Aggregated Models

These models are for homicide data aggregated from 2001 - 2017

library(INLA)

Loading required package: sp
package ‘sp’ was built under R version 3.4.1Loading required package: Matrix
This is INLA_17.06.20 built 2017-06-20 03:44:36 UTC.
See www.r-inla.org/contact-us for how to get help.

library(dplyr)

package ‘dplyr’ was built under R version 3.4.4
Attaching package: ‘dplyr’

The following objects are masked from ‘package:stats’:

    filter, lag

The following objects are masked from ‘package:base’:

    intersect, setdiff, setequal, union

library(readr)
library(stringi)

package ‘stringi’ was built under R version 3.4.4

library(rgdal)

package ‘rgdal’ was built under R version 3.4.4rgdal: version: 1.2-18, (SVN revision 718)
 Geospatial Data Abstraction Library extensions to R successfully loaded
 Loaded GDAL runtime: GDAL 2.1.3, released 2017/20/01
 Path to GDAL shared files: /Library/Frameworks/R.framework/Versions/3.4/Resources/library/rgdal/gdal
 GDAL binary built with GEOS: FALSE 
 Loaded PROJ.4 runtime: Rel. 4.9.3, 15 August 2016, [PJ_VERSION: 493]
 Path to PROJ.4 shared files: /Library/Frameworks/R.framework/Versions/3.4/Resources/library/rgdal/proj
 Linking to sp version: 1.2-7 

library(spdep)

package ‘spdep’ was built under R version 3.4.4Loading required package: spData
package ‘spData’ was built under R version 3.4.4To access larger datasets in this package, install the spDataLarge package with:
`install.packages('spDataLarge', repos='https://nowosad.github.io/drat/',
type='source'))`

plot_fort_maps2 <- function(data, fill_str, legend_title, plot_title, size=0.1){
  require(ggplot2)
  require(ggsn)
  require(broom)
  ggplot() +                                               # initialize ggplot object
    geom_polygon(                                          # make a polygon
      data = data,                                    # data frame
      aes_string(x = "long", y = "lat", group = "group",                # coordinates, and group them by polygons
                 fill = fill_str),
      size=size, color="black") +                # variable to use for filling
    scale_fill_brewer(name=legend_title, palette = "RdYlBu", direction = -1,
                      drop = FALSE) + # fill with brewer colors   # add title
    theme(line = element_blank(),
          axis.text=element_blank(),      # .. tickmarks..
          axis.title=element_blank(),
          legend.position="none",
          plot.margin = unit(c(0, 0, 0, 0), "cm"),
          #legend.text=element_text(size=15),
          #legend.title=element_text(size=17), # .. axis labels..
          panel.background = element_blank(), plot.title = element_text(size=5)) + ggtitle(plot_title)
}
shape_to_ggplot <- function(shape){
  require(broom)
  gg_data <- tidy(shape)
  data <- slot(shape, "data")
  shape[["polyID"]] <- sapply(slot(shape, "polygons"), function(x) slot(x, "ID"))
  gg_data <- merge(gg_data, shape, by.x="id", by.y="polyID")
  return(gg_data)
}

SMR_data <- read_csv("~/Documents/Harvard - SM80/Thesis/Fortaleza_Hom_RGit_PRIVATE_Files/CT_SMR_per_mnth_MISSING_ADJ.csv",
    col_types = cols(CD_GEOCODI = col_character()))
CT_shp <- readOGR("~/Documents/Harvard - SM80/Thesis/Fortaleza_Hom_RGit_PRIVATE_Files/Shapefiles/Shapefiles/CTs/", "Corrected_CTs", use_iconv = TRUE, encoding = "latin1")

OGR data source with driver: ESRI Shapefile 
Source: "/Users/Sudipta/Documents/Harvard - SM80/Thesis/Fortaleza_Hom_RGit_PRIVATE_Files/Shapefiles/Shapefiles/CTs", layer: "Corrected_CTs"
with 3044 features
It has 13 fields

CT_shp_gg <- shape_to_ggplot(CT_shp)

Loading required package: broom
package ‘broom’ was built under R version 3.4.4Regions defined for each Polygons

Some CTs have homicides but non pop. We have to revisit these. For now, I am turning Inf IR and SMR to zero. At most there are 2 homicides per year in these CTs. Also NaN are pop zero, hom zero. Also turning these to zero.

SMR_data <- SMR_data  %>%
  group_by(CD_GEOCODI) %>%
  summarize(y=sum(y), E=sum(E)) %>% 
  mutate(SMR=y/E) %>% 
  mutate(SMR=replace(SMR, SMR==Inf | is.nan(SMR), 0)) %>% as.data.frame() %>% rename(obs_count=y, exp_count=E)

package ‘bindrcpp’ was built under R version 3.4.4

library(epitools)

package ‘epitools’ was built under R version 3.4.2

SMR_data$SMR_var <- SMR_data$obs_count / (SMR_data$exp_count)^2
SMR_data$CI95_lower <- NA
SMR_data$CI95_upper <- NA
SMR_data[,c("CI95_lower", "CI95_upper")] <- pois.exact(x=SMR_data$obs_count, pt=SMR_data$exp_count, conf.level=0.95)[,c(4,5)]

CT_shp@data$CD_GEOCODI <- as.character(CT_shp@data$CD_GEOCODI)
CT_shp@data <- arrange(CT_shp@data, CD_GEOCODI)
CT_wm <- poly2nb(CT_shp, snap=0.001)
nb2INLA("CT_graph.adj", CT_wm)
CT_adj <- "CT_graph.adj"

Some CTs have homicides but non pop. We have to revisit these. For now, I am turning Inf IR and SMR to zero. At most there are 2 homicides per year in these CTs. Also NaN are pop zero, hom zero. Also turning these to zero. Also turning counts to zero if underlying population is zero

BYM_data <- SMR_data %>% rename(y=obs_count, E=exp_count) %>% right_join(CT_shp@data, by="CD_GEOCODI") %>% mutate(y=replace(y, is.na(y), 0), E=replace(E, is.na(E), 0)) %>% dplyr::select(CD_GEOCODI, y, E) %>% arrange(CD_GEOCODI) %>% mutate(bymID=1:3044)

formula_poisson_null <- y ~ 1 + f(bymID, model="iid")
model_poisson_null <- inla(formula_poisson_null, family="poisson", data=BYM_data, E=E, control.predictor=list(compute=TRUE), control.compute = list(dic = TRUE), verbose = TRUE)

    hgid: 29c6a7f1b1ff  date: Thu Jun 15 19:50:23 2017 +0800
Report bugs to <help@r-inla.org>
Processing file [/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/Model.ini] max_threads=[4]
inla_build...
    number of sections=[8]
    parse section=[0] name=[INLA.libR] type=[LIBR]
    inla_parse_libR...
        section[INLA.libR]
            R_HOME=[/Library/Frameworks/R.framework/Resources]
    parse section=[7] name=[INLA.Expert] type=[EXPERT]
    inla_parse_expert...
        section[INLA.Expert]
            disable.gaussian.check=[0]
            cpo.manual=[0]
            jp.Rfile=[(null)]
            jp.RData=NULL
            jp.func=[(null)]
    parse section=[1] name=[INLA.Model] type=[PROBLEM]
    inla_parse_problem...
        name=[INLA.Model]
        openmp.strategy=[default]
    store results in directory=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/results.files]
        output:
            cpo=[0]
            po=[0]
            dic=[1]
            kld=[1]
            mlik=[1]
            q=[0]
            graph=[0]
            gdensity=[0]
            hyperparameters=[1]
            summary=[1]
            return.marginals=[1]
            nquantiles=[3]  [ 0.025 0.5 0.975 ]
            ncdf=[0]  [ ]
    parse section=[3] name=[Predictor] type=[PREDICTOR]
    inla_parse_predictor ...
        section=[Predictor]
        dir=[predictor]
        PRIOR->name=[loggamma]
        hyperid=[53001|Predictor]
        PRIOR->from_theta=[function (x) <<NEWLINE>>exp(x)]
        PRIOR->to_theta = [function (x) <<NEWLINE>>log(x)]
        PRIOR->PARAMETERS=[1, 1e-05]
        initialise log_precision[12]
        fixed=[1]
        user.scale=[1]
        n=[3044]
        m=[0]
        ndata=[3044]
        compute=[1]
        read offsets from file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f49449ea1]
        read n=[6088] entries from file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f49449ea1]
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f49449ea1] 0/3044  (idx,y) = (0, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f49449ea1] 1/3044  (idx,y) = (1, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f49449ea1] 2/3044  (idx,y) = (2, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f49449ea1] 3/3044  (idx,y) = (3, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f49449ea1] 4/3044  (idx,y) = (4, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f49449ea1] 5/3044  (idx,y) = (5, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f49449ea1] 6/3044  (idx,y) = (6, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f49449ea1] 7/3044  (idx,y) = (7, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f49449ea1] 8/3044  (idx,y) = (8, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f49449ea1] 9/3044  (idx,y) = (9, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f49449ea1] 10/3044  (idx,y) = (10, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f49449ea1] 11/3044  (idx,y) = (11, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f49449ea1] 12/3044  (idx,y) = (12, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f49449ea1] 13/3044  (idx,y) = (13, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f49449ea1] 14/3044  (idx,y) = (14, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f49449ea1] 15/3044  (idx,y) = (15, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f49449ea1] 16/3044  (idx,y) = (16, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f49449ea1] 17/3044  (idx,y) = (17, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f49449ea1] 18/3044  (idx,y) = (18, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f49449ea1] 19/3044  (idx,y) = (19, 0)
        Aext=[(null)]
        AextPrecision=[1e+08]
        output:
            summary=[1]
            return.marginals=[1]
            nquantiles=[3]  [ 0.025 0.5 0.975 ]
            ncdf=[0]  [ ]
    parse section=[2] name=[INLA.Data1] type=[DATA]
    inla_parse_data [section 1]...
        tag=[INLA.Data1]
        family=[POISSON]
        likelihood=[POISSON]
        file->name=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f66f63d7a]
        file->name=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f303e4965]
        read n=[9132] entries from file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f66f63d7a]
            0/3044  (idx,a,y,d) = (0, 14.827, 12, 1)
            1/3044  (idx,a,y,d) = (1, 4.88122, 4, 1)
            2/3044  (idx,a,y,d) = (2, 9.75508, 31, 1)
            3/3044  (idx,a,y,d) = (3, 10.764, 10, 1)
            4/3044  (idx,a,y,d) = (4, 7.50958, 5, 1)
            5/3044  (idx,a,y,d) = (5, 7.69529, 9, 1)
            6/3044  (idx,a,y,d) = (6, 4.62971, 7, 1)
            7/3044  (idx,a,y,d) = (7, 6.07998, 11, 1)
            8/3044  (idx,a,y,d) = (8, 5.20853, 6, 1)
            9/3044  (idx,a,y,d) = (9, 9.1703, 1, 1)
            10/3044  (idx,a,y,d) = (10, 5.07622, 5, 1)
            11/3044  (idx,a,y,d) = (11, 5.27241, 1, 1)
            12/3044  (idx,a,y,d) = (12, 2.71774, 4, 1)
            13/3044  (idx,a,y,d) = (13, 3.94485, 1, 1)
            14/3044  (idx,a,y,d) = (14, 6.43779, 3, 1)
            15/3044  (idx,a,y,d) = (15, 5.35615, 4, 1)
            16/3044  (idx,a,y,d) = (16, 8.77675, 2, 1)
            17/3044  (idx,a,y,d) = (17, 5.14462, 2, 1)
            18/3044  (idx,a,y,d) = (18, 5.87517, 1, 1)
            19/3044  (idx,a,y,d) = (19, 5.50689, 3, 1)
        likelihood.variant=[0]
        Link model   [LOG]
        Link order   [-1]
        Link variant [-1]
        Link ntheta  [0]
        mix.use[0]
    parse section=[5] name=[bymID] type=[FFIELD]
    inla_parse_ffield...
        section=[bymID]
        dir=[random.effect00000001]
        model=[iid]
        PRIOR->name=[loggamma]
        hyperid=[1001|bymID]
        PRIOR->from_theta=[function (x) <<NEWLINE>>exp(x)]
        PRIOR->to_theta = [function (x) <<NEWLINE>>log(x)]
        PRIOR->PARAMETERS=[1, 5e-05]
        correct=[-1]
        constr=[0]
        diagonal=[0]
        id.names=<not present>
        compute=[1]
        nrep=[1]
        ngroup=[1]
        read covariates from file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f214c4a]
        read n=[6088] entries from file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f214c4a]
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f214c4a] 0/3044  (idx,y) = (0, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f214c4a] 1/3044  (idx,y) = (1, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f214c4a] 2/3044  (idx,y) = (2, 2)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f214c4a] 3/3044  (idx,y) = (3, 3)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f214c4a] 4/3044  (idx,y) = (4, 4)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f214c4a] 5/3044  (idx,y) = (5, 5)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f214c4a] 6/3044  (idx,y) = (6, 6)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f214c4a] 7/3044  (idx,y) = (7, 7)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f214c4a] 8/3044  (idx,y) = (8, 8)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f214c4a] 9/3044  (idx,y) = (9, 9)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f214c4a] 10/3044  (idx,y) = (10, 10)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f214c4a] 11/3044  (idx,y) = (11, 11)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f214c4a] 12/3044  (idx,y) = (12, 12)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f214c4a] 13/3044  (idx,y) = (13, 13)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f214c4a] 14/3044  (idx,y) = (14, 14)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f214c4a] 15/3044  (idx,y) = (15, 15)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f214c4a] 16/3044  (idx,y) = (16, 16)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f214c4a] 17/3044  (idx,y) = (17, 17)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f214c4a] 18/3044  (idx,y) = (18, 18)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f214c4a] 19/3044  (idx,y) = (19, 19)
        file for locations=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f39c303db]
            nlocations=[3044]
            locations[0]=[1]
            locations[1]=[2]
            locations[2]=[3]
            locations[3]=[4]
            locations[4]=[5]
            locations[5]=[6]
            locations[6]=[7]
            locations[7]=[8]
            locations[8]=[9]
            locations[9]=[10]
            locations[10]=[11]
            locations[11]=[12]
            locations[12]=[13]
            locations[13]=[14]
            locations[14]=[15]
            locations[15]=[16]
            locations[16]=[17]
            locations[17]=[18]
            locations[18]=[19]
            locations[19]=[20]
        cyclic=[0]
        initialise log_precision[4]
        fixed=[0]
        computed/guessed rank-deficiency = [0]
        output:
            summary=[1]
            return.marginals=[1]
            nquantiles=[3]  [ 0.025 0.5 0.975 ]
            ncdf=[0]  [ ]
    section=[4] name=[(Intercept)] type=[LINEAR]
    inla_parse_linear...
        section[(Intercept)]
        dir=[fixed.effect00000001]
        file for covariates=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f380a819b]
        read n=[6088] entries from file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f380a819b]
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f380a819b] 0/3044  (idx,y) = (0, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f380a819b] 1/3044  (idx,y) = (1, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f380a819b] 2/3044  (idx,y) = (2, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f380a819b] 3/3044  (idx,y) = (3, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f380a819b] 4/3044  (idx,y) = (4, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f380a819b] 5/3044  (idx,y) = (5, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f380a819b] 6/3044  (idx,y) = (6, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f380a819b] 7/3044  (idx,y) = (7, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f380a819b] 8/3044  (idx,y) = (8, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f380a819b] 9/3044  (idx,y) = (9, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f380a819b] 10/3044  (idx,y) = (10, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f380a819b] 11/3044  (idx,y) = (11, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f380a819b] 12/3044  (idx,y) = (12, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f380a819b] 13/3044  (idx,y) = (13, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f380a819b] 14/3044  (idx,y) = (14, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f380a819b] 15/3044  (idx,y) = (15, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f380a819b] 16/3044  (idx,y) = (16, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f380a819b] 17/3044  (idx,y) = (17, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f380a819b] 18/3044  (idx,y) = (18, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/data.files/filef0f380a819b] 19/3044  (idx,y) = (19, 1)
        prior mean=[0]
        prior precision=[0]
        compute=[1]
        output:
            summary=[1]
            return.marginals=[1]
            nquantiles=[3]  [ 0.025 0.5 0.975 ]
            ncdf=[0]  [ ]
    Index table: number of entries[3], total length[6089]
        tag                            start-index     length
        Predictor                               0       3044
        bymID                                3044       3044
        (Intercept)                          6088          1
    parse section=[6] name=[INLA.Parameters] type=[INLA]
    inla_parse_INLA...
        section[INLA.Parameters]
            lincomb.derived.only = [Yes]
            lincomb.derived.correlation.matrix = [No]
        global_node.factor = 2.000
        global_node.degree = 2147483647
        reordering = -1
Contents of ai_param 0x7fe8d16059f0
    Optimiser: DEFAULT METHOD
        Option for domin-BFGS: epsx = 0.005
        Option for domin-BFGS: epsf = 1e-05 (rounding error)
        Option for domin-BFGS: epsg = 0.005
        Option for GSL-BFGS2: tol  = 0.1
        Option for GSL-BFGS2: step_size = 1
        Option for GSL-BFGS2: epsx = 0.005
        Option for GSL-BFGS2: epsf = 0.000353553
        Option for GSL-BFGS2: epsg = 0.005
        Restart: 0
        Mode known: No
    Gaussian approximation:
        abserr_func = 0.0005
        abserr_step = 0.0005
        optpar_fp = 0
        optpar_nr_step_factor = -0.1
    Gaussian data: No
    Strategy:   Use a mean-skew corrected Gaussian by fitting a Skew-Normal
    Fast mode:  On
    Use linear approximation to log(|Q +c|)? Yes
        Method:  Compute the derivative exact
    Parameters for improved approximations
        Number of points evaluate:   9
        Step length to compute derivatives numerically:  0.000100002
        Stencil to compute derivatives numerically:  5
        Cutoff value to construct local neigborhood:     0.0001
    Log calculations:    On
    Log calculated marginal for the hyperparameters:     On
    Integration strategy:    Automatic (GRID for dim(theta)=1 and 2 and otherwise CCD)
        f0 (CCD only):   1.100000
        dz (GRID only):  0.750000
        Adjust weights (GRID only):  On
        Difference in log-density limit (GRID only):     6.000000
        Skip configurations with (presumed) small density (GRID only):   On
    Gradient is computed using Central difference with step-length 0.010000
    Hessian is computed using Central difference with step-length 0.100000
    Hessian matrix is forced to be a diagonal matrix? [No]
    Compute effective number of parameters? [Yes]
    Perform a Monte Carlo error-test? [No]
    Interpolator [Auto]
    CPO required diff in log-density [3]
    Stupid search mode:
        Status     [On]
        Max iter   [1000]
        Factor     [1.05]
    Numerical integration of hyperparameters:
        Maximum number of function evaluations [100000]
        Relative error ....................... [1e-05]
        Absolute error ....................... [1e-06]
    To stabilise the numerical optimisation:
        Minimum value of the -Hessian [-inf]
    CPO manual calculation[No]
    Laplace-correction is Disabled.

inla_build: check for unused entries in[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/Model.ini]
inla_INLA...
    Strategy = [DEFAULT]
    Size is [6089]
    Chose OpenMP-strategy [LARGE]
    Chose density-strategy [HIGH]
    Size of graph=[6089] constraints=[0]
    Found optimal reordering=[amdc] nnz(L)=[15221] and use_global_nodes(user)=[no]
    List of hyperparameters: 
        theta[0] = [Log precision for bymID]
Optimise using DEFAULT METHOD
max.logdens= -12594.216580 fn= 1 theta= 3.990000  range=[-0.188 2.852]
max.logdens= -10970.805657 fn= 3 theta= 3.000000  range=[-0.415 3.617]
max.logdens= -10953.743044 fn= 4 theta= 2.990000  range=[-0.418 3.622]
max.logdens= -8451.523025 fn= 6 theta= 0.829830  range=[-1.422 5.356]
max.logdens= -8447.884013 fn= 7 theta= 0.819830  range=[-1.428 5.359]
max.logdens= -8364.982909 fn= 10 theta= 0.263314  range=[-1.771 5.501]
max.logdens= -8364.478189 fn= 11 theta= 0.273314  range=[-1.765 5.499]
Iter=1 |grad|=53.3 |x-x.old|=3.74 |f-f.old|=4.24e+03 
max.logdens= -8363.167032 fn= 14 theta= 0.334507  range=[-1.726 5.486]
max.logdens= -8363.015325 fn= 15 theta= 0.324507  range=[-1.732 5.488]
max.logdens= -8362.943552 fn= 16 theta= 0.344507  range=[-1.719 5.483]
Iter=2 |grad|=3.59 |x-x.old|=0.0712 |f-f.old|=1.82 
Iter=3 |grad|=0.069 |x-x.old|=0.00498(pass) |f-f.old|=0.198 
Number of function evaluations = 21
Compute the Hessian using central differences and step_size[0.1]. Matrix-type [dense]

   717.946269
Eigenvectors of the Hessian
    1.000000
Eigenvalues of the Hessian
    717.946269
StDev/Correlation matrix (scaled inverse Hessian)
     0.037321
Compute corrected stdev for theta[0]: negative 0.986960  positive 0.996278
max.logdens= -8362.935007 fn= 27 theta= 0.339488  range=[-1.723 5.484]
max.logdens= -8362.933247 fn= 28 theta= 0.339488  range=[-1.723 5.484]
    config  0=[  0.00] log(rel.dens)= 0.00, [3] accept, compute, 2.17s
    config  1=[  0.75] log(rel.dens)=-0.46, [1] accept, compute, 2.29s
    config  2=[ -0.75] log(rel.dens)=-0.29, [2] accept, compute, 2.32s
    config  3=[  1.50] log(rel.dens)=-1.11, [0] accept, compute, 2.34s
    config  4=[ -1.50] log(rel.dens)=-1.16, [3] accept, compute, 2.37s
    config  5=[  3.00] log(rel.dens)=-4.52, [0] accept, compute, 2.31s
    config  6=[  2.25] log(rel.dens)=-2.56, [1] accept, compute, 2.39s
    config  7=[ -2.25] log(rel.dens)=-2.53, [2] accept, compute, 2.36s
    config  8=[  3.75] log(rel.dens)=-7.02, reject, 0.06s
    config  9=[ -4.50] log(rel.dens)=-9.95, reject, 0.06s
    config 10=[ -3.75] log(rel.dens)=-6.84, reject, 0.09s
    config 11=[ -5.25] log(rel.dens)=-13.33, reject, 0.08s
    config 12=[ -3.00] log(rel.dens)=-4.45, [3] accept, compute, 1.24s
Combine the densities with relative weights:
    config  0/ 9=[  0.00] weight = 1.000 adjusted weight = 0.977  neff = 2174.87
    config  1/ 9=[  0.75] weight = 0.632 adjusted weight = 0.625  neff = 2162.28
    config  2/ 9=[ -0.75] weight = 0.747 adjusted weight = 0.739  neff = 2187.46
    config  3/ 9=[  1.50] weight = 0.328 adjusted weight = 0.337  neff = 2149.27
    config  4/ 9=[ -1.50] weight = 0.313 adjusted weight = 0.322  neff = 2199.94
    config  5/ 9=[  3.00] weight = 0.011 adjusted weight = 0.013  neff = 2123.14
    config  6/ 9=[  2.25] weight = 0.077 adjusted weight = 0.085  neff = 2136.29
    config  7/ 9=[ -2.25] weight = 0.079 adjusted weight = 0.087  neff = 2212.23
    config  8/ 9=[ -3.00] weight = 0.012 adjusted weight = 0.014  neff = 2224.39
Done.
Expected effective number of parameters: 2175.145(17.278),  eqv.#replicates: 1.399
DIC:
    Mean of Deviance................. 12419.3
    Deviance at Mean................. 10279.8
    Effective number of parameters... 2139.48
    DIC.............................. 14558.7
Marginal likelihood: Integration -8365.348296 Gaussian-approx -8365.304266
Compute the marginal for each of the 1 hyperparameters
Interpolation method: Auto
    Compute the marginal for theta[0] to theta[0] using numerical integration...
    Compute the marginal for theta[0] to theta[0] using numerical integration... Done.
Compute the marginal for the hyperparameters... done.
Store results in directory[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/results.files]

Wall-clock time used on [/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f6735767d/Model.ini]
    Preparations    :   0.062 seconds
    Approx inference:   7.699 seconds [3.0|0.0|15.0|75.3|6.7]%
    Output          :   0.499 seconds
    ---------------------------------
    Total           :   8.261 seconds

Plot smoothed and unsmoothed rates

breaks <- c(0,0.1,0.25,0.5,0.75,1,1.5,2.5,3,5,202)
CT_shp_gg_SMR <- CT_shp_gg[,-1] %>% left_join(SMR_data[,c(1,4)], by="CD_GEOCODI") %>% mutate(cut=cut(SMR, breaks=breaks, labels=(c("[0,0.1]","(0.1,0.25]","(0.25,0.5]","(0.5,0.75]","(0.75,1]","(1,1.5]","(1.5,2.5]","(2.5,3]","(3,5]", ">5")), include.lowest=TRUE))

Column `CD_GEOCODI` joining factor and character vector, coercing into character vector

plot_fort_maps2(CT_shp_gg_SMR, "cut","Unsmoothed SMR", "Aggregate SMR for 2001-17 by CT") + theme(plot.title = element_text(size=10), legend.position = "right")

library(RColorBrewer)
set.seed(2014)
plot(1,1, type="n", xlim=c(500,650), ylim=c(0,10),
  main= "Confidence intervals of the SMR",
  xlab="County", ylab="Relative Risk", xaxt="n")
abline(h=1, lty=2)

for(i in 500:650){
  if(!is.na(SMR_data$exp_count[i])){
        if(SMR_data$CI95_lower[i]>1 ) {
            sig.col <- brewer.pal(4, "Reds")[4]
            col <- sig.col
            lty <- 2
            #text(i, SMR_data$CI95_upper[i]+.31,
                #srt=90, col=sig.col, cex=.85)
        } else {
            col <- "black"
            lty <- 1
        }
        lines(c(i,i), c(SMR_data$CI95_lower[i],SMR_data$CI95_upper[i]), col=col, lty=lty)
        points(x=i, y=SMR_data$SMR_17yr[i], pch=18, col=col)
  }
}

breaks <- c(0,0.1,0.25,0.5,0.75,1,1.5,2.5,3,5,202)
results <- data.frame(bymID=BYM_data$bymID, CD_GEOCODI=BYM_data$CD_GEOCODI, fit_SMR = model_poisson_null$summary.fitted.values$mean)
CT_shp_gg_SMR_smth <- CT_shp_gg_SMR %>% left_join(results, by="CD_GEOCODI") %>% mutate(fit_cut=cut(fit_SMR, breaks=breaks, labels=(c("[0,0.1]","(0.1,0.25]","(0.25,0.5]","(0.5,0.75]","(0.75,1]","(1,1.5]","(1.5,2.5]","(2.5,3]","(3,5]", ">5")), include.lowest=TRUE))

Column `CD_GEOCODI` joining character vector and factor, coercing into character vector

plot_fort_maps2(CT_shp_gg_SMR_smth, "fit_cut","Fitted SMR", "Aggregate Poisson smoothed SMR for 2001-17 by CT") + theme(plot.title = element_text(size=10), legend.position = "right")

formula_bym_null <- y ~ f(bymID, model="bym", graph=CT_adj)
model_bym_null <- inla(formula_bym_null, family="poisson", data=BYM_data, E=E, control.predictor=list(compute=TRUE), control.compute = list(dic = TRUE), verbose = TRUE)

    hgid: 29c6a7f1b1ff  date: Thu Jun 15 19:50:23 2017 +0800
Report bugs to <help@r-inla.org>
Processing file [/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/Model.ini] max_threads=[4]
inla_build...
    number of sections=[8]
    parse section=[0] name=[INLA.libR] type=[LIBR]
    inla_parse_libR...
        section[INLA.libR]
            R_HOME=[/Library/Frameworks/R.framework/Resources]
    parse section=[7] name=[INLA.Expert] type=[EXPERT]
    inla_parse_expert...
        section[INLA.Expert]
            disable.gaussian.check=[0]
            cpo.manual=[0]
            jp.Rfile=[(null)]
            jp.RData=NULL
            jp.func=[(null)]
    parse section=[1] name=[INLA.Model] type=[PROBLEM]
    inla_parse_problem...
        name=[INLA.Model]
        openmp.strategy=[default]
    store results in directory=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/results.files]
        output:
            cpo=[0]
            po=[0]
            dic=[1]
            kld=[1]
            mlik=[1]
            q=[0]
            graph=[0]
            gdensity=[0]
            hyperparameters=[1]
            summary=[1]
            return.marginals=[1]
            nquantiles=[3]  [ 0.025 0.5 0.975 ]
            ncdf=[0]  [ ]
    parse section=[3] name=[Predictor] type=[PREDICTOR]
    inla_parse_predictor ...
        section=[Predictor]
        dir=[predictor]
        PRIOR->name=[loggamma]
        hyperid=[53001|Predictor]
        PRIOR->from_theta=[function (x) <<NEWLINE>>exp(x)]
        PRIOR->to_theta = [function (x) <<NEWLINE>>log(x)]
        PRIOR->PARAMETERS=[1, 1e-05]
        initialise log_precision[12]
        fixed=[1]
        user.scale=[1]
        n=[3044]
        m=[0]
        ndata=[3044]
        compute=[1]
        read offsets from file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f496b41ce]
        read n=[6088] entries from file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f496b41ce]
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f496b41ce] 0/3044  (idx,y) = (0, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f496b41ce] 1/3044  (idx,y) = (1, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f496b41ce] 2/3044  (idx,y) = (2, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f496b41ce] 3/3044  (idx,y) = (3, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f496b41ce] 4/3044  (idx,y) = (4, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f496b41ce] 5/3044  (idx,y) = (5, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f496b41ce] 6/3044  (idx,y) = (6, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f496b41ce] 7/3044  (idx,y) = (7, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f496b41ce] 8/3044  (idx,y) = (8, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f496b41ce] 9/3044  (idx,y) = (9, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f496b41ce] 10/3044  (idx,y) = (10, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f496b41ce] 11/3044  (idx,y) = (11, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f496b41ce] 12/3044  (idx,y) = (12, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f496b41ce] 13/3044  (idx,y) = (13, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f496b41ce] 14/3044  (idx,y) = (14, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f496b41ce] 15/3044  (idx,y) = (15, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f496b41ce] 16/3044  (idx,y) = (16, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f496b41ce] 17/3044  (idx,y) = (17, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f496b41ce] 18/3044  (idx,y) = (18, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f496b41ce] 19/3044  (idx,y) = (19, 0)
        Aext=[(null)]
        AextPrecision=[1e+08]
        output:
            summary=[1]
            return.marginals=[1]
            nquantiles=[3]  [ 0.025 0.5 0.975 ]
            ncdf=[0]  [ ]
    parse section=[2] name=[INLA.Data1] type=[DATA]
    inla_parse_data [section 1]...
        tag=[INLA.Data1]
        family=[POISSON]
        likelihood=[POISSON]
        file->name=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f1081f6ee]
        file->name=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f447a8bb9]
        read n=[9132] entries from file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f1081f6ee]
            0/3044  (idx,a,y,d) = (0, 14.827, 12, 1)
            1/3044  (idx,a,y,d) = (1, 4.88122, 4, 1)
            2/3044  (idx,a,y,d) = (2, 9.75508, 31, 1)
            3/3044  (idx,a,y,d) = (3, 10.764, 10, 1)
            4/3044  (idx,a,y,d) = (4, 7.50958, 5, 1)
            5/3044  (idx,a,y,d) = (5, 7.69529, 9, 1)
            6/3044  (idx,a,y,d) = (6, 4.62971, 7, 1)
            7/3044  (idx,a,y,d) = (7, 6.07998, 11, 1)
            8/3044  (idx,a,y,d) = (8, 5.20853, 6, 1)
            9/3044  (idx,a,y,d) = (9, 9.1703, 1, 1)
            10/3044  (idx,a,y,d) = (10, 5.07622, 5, 1)
            11/3044  (idx,a,y,d) = (11, 5.27241, 1, 1)
            12/3044  (idx,a,y,d) = (12, 2.71774, 4, 1)
            13/3044  (idx,a,y,d) = (13, 3.94485, 1, 1)
            14/3044  (idx,a,y,d) = (14, 6.43779, 3, 1)
            15/3044  (idx,a,y,d) = (15, 5.35615, 4, 1)
            16/3044  (idx,a,y,d) = (16, 8.77675, 2, 1)
            17/3044  (idx,a,y,d) = (17, 5.14462, 2, 1)
            18/3044  (idx,a,y,d) = (18, 5.87517, 1, 1)
            19/3044  (idx,a,y,d) = (19, 5.50689, 3, 1)
        likelihood.variant=[0]
        Link model   [LOG]
        Link order   [-1]
        Link variant [-1]
        Link ntheta  [0]
        mix.use[0]
    parse section=[5] name=[bymID] type=[FFIELD]
    inla_parse_ffield...
        section=[bymID]
        dir=[random.effect00000001]
        model=[bym]
        PRIOR0->name=[loggamma]
        hyperid=[10001|bymID]
        PRIOR0->from_theta=[function (x) <<NEWLINE>>exp(x)]
        PRIOR0->to_theta = [function (x) <<NEWLINE>>log(x)]
        PRIOR0->PARAMETERS0=[1, 0.0005]
        PRIOR1->name=[loggamma]
        hyperid=[10002|bymID]
        PRIOR1->from_theta=[function (x) <<NEWLINE>>exp(x)]
        PRIOR1->to_theta = [function (x) <<NEWLINE>>log(x)]
        PRIOR1->PARAMETERS1=[1, 0.0005]
        correct=[-1]
        constr=[0]
        diagonal=[1.01511e-05]
        id.names=<not present>
        compute=[1]
        nrep=[1]
        ngroup=[1]
        read covariates from file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f6700e642]
        read n=[6088] entries from file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f6700e642]
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f6700e642] 0/3044  (idx,y) = (0, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f6700e642] 1/3044  (idx,y) = (1, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f6700e642] 2/3044  (idx,y) = (2, 2)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f6700e642] 3/3044  (idx,y) = (3, 3)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f6700e642] 4/3044  (idx,y) = (4, 4)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f6700e642] 5/3044  (idx,y) = (5, 5)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f6700e642] 6/3044  (idx,y) = (6, 6)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f6700e642] 7/3044  (idx,y) = (7, 7)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f6700e642] 8/3044  (idx,y) = (8, 8)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f6700e642] 9/3044  (idx,y) = (9, 9)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f6700e642] 10/3044  (idx,y) = (10, 10)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f6700e642] 11/3044  (idx,y) = (11, 11)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f6700e642] 12/3044  (idx,y) = (12, 12)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f6700e642] 13/3044  (idx,y) = (13, 13)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f6700e642] 14/3044  (idx,y) = (14, 14)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f6700e642] 15/3044  (idx,y) = (15, 15)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f6700e642] 16/3044  (idx,y) = (16, 16)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f6700e642] 17/3044  (idx,y) = (17, 17)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f6700e642] 18/3044  (idx,y) = (18, 18)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f6700e642] 19/3044  (idx,y) = (19, 19)
        read graph from file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f117a0105]
        file for locations=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f56bde848]
            nlocations=[3044]
            locations[0]=[1]
            locations[1]=[2]
            locations[2]=[3]
            locations[3]=[4]
            locations[4]=[5]
            locations[5]=[6]
            locations[6]=[7]
            locations[7]=[8]
            locations[8]=[9]
            locations[9]=[10]
            locations[10]=[11]
            locations[11]=[12]
            locations[12]=[13]
            locations[13]=[14]
            locations[14]=[15]
            locations[15]=[16]
            locations[16]=[17]
            locations[17]=[18]
            locations[18]=[19]
            locations[19]=[20]
        initialise log_precision (iid component)[4]
        fixed=[0]
        initialise log_precision (spatial component)[4]
        fixed=[0]
        adjust.for.con.comp[1]
        scale.model[0]
        read extra constraint from file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f6c0d2be2]
        Constraint[0]
            A[3044] = 1.000000
            A[3045] = 1.000000
            A[3046] = 1.000000
            A[3047] = 1.000000
            A[3048] = 1.000000
            A[3049] = 1.000000
            A[3050] = 1.000000
            A[3051] = 1.000000
            A[3052] = 1.000000
            A[3053] = 1.000000
            A[3054] = 1.000000
            A[3055] = 1.000000
            A[3056] = 1.000000
            A[3057] = 1.000000
            A[3058] = 1.000000
            A[3059] = 1.000000
            A[3060] = 1.000000
            A[3061] = 1.000000
            A[3062] = 1.000000
            A[3063] = 1.000000
            A[3064] = 1.000000
            e[0] = 0.000000
        rank-deficiency is *defined* [1]
        output:
            summary=[1]
            return.marginals=[1]
            nquantiles=[3]  [ 0.025 0.5 0.975 ]
            ncdf=[0]  [ ]
    section=[4] name=[(Intercept)] type=[LINEAR]
    inla_parse_linear...
        section[(Intercept)]
        dir=[fixed.effect00000001]
        file for covariates=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f20ad610a]
        read n=[6088] entries from file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f20ad610a]
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f20ad610a] 0/3044  (idx,y) = (0, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f20ad610a] 1/3044  (idx,y) = (1, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f20ad610a] 2/3044  (idx,y) = (2, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f20ad610a] 3/3044  (idx,y) = (3, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f20ad610a] 4/3044  (idx,y) = (4, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f20ad610a] 5/3044  (idx,y) = (5, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f20ad610a] 6/3044  (idx,y) = (6, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f20ad610a] 7/3044  (idx,y) = (7, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f20ad610a] 8/3044  (idx,y) = (8, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f20ad610a] 9/3044  (idx,y) = (9, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f20ad610a] 10/3044  (idx,y) = (10, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f20ad610a] 11/3044  (idx,y) = (11, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f20ad610a] 12/3044  (idx,y) = (12, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f20ad610a] 13/3044  (idx,y) = (13, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f20ad610a] 14/3044  (idx,y) = (14, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f20ad610a] 15/3044  (idx,y) = (15, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f20ad610a] 16/3044  (idx,y) = (16, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f20ad610a] 17/3044  (idx,y) = (17, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f20ad610a] 18/3044  (idx,y) = (18, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/data.files/filef0f20ad610a] 19/3044  (idx,y) = (19, 1)
        prior mean=[0]
        prior precision=[0]
        compute=[1]
        output:
            summary=[1]
            return.marginals=[1]
            nquantiles=[3]  [ 0.025 0.5 0.975 ]
            ncdf=[0]  [ ]
    Index table: number of entries[3], total length[9133]
        tag                            start-index     length
        Predictor                               0       3044
        bymID                                3044       6088
        (Intercept)                          9132          1
    parse section=[6] name=[INLA.Parameters] type=[INLA]
    inla_parse_INLA...
        section[INLA.Parameters]
            lincomb.derived.only = [Yes]
            lincomb.derived.correlation.matrix = [No]
        global_node.factor = 2.000
        global_node.degree = 2147483647
        reordering = -1
Contents of ai_param 0x7fe401701710
    Optimiser: DEFAULT METHOD
        Option for domin-BFGS: epsx = 0.005
        Option for domin-BFGS: epsf = 1e-05 (rounding error)
        Option for domin-BFGS: epsg = 0.005
        Option for GSL-BFGS2: tol  = 0.1
        Option for GSL-BFGS2: step_size = 1
        Option for GSL-BFGS2: epsx = 0.005
        Option for GSL-BFGS2: epsf = 0.000353553
        Option for GSL-BFGS2: epsg = 0.005
        Restart: 0
        Mode known: No
    Gaussian approximation:
        abserr_func = 0.0005
        abserr_step = 0.0005
        optpar_fp = 0
        optpar_nr_step_factor = -0.1
    Gaussian data: No
    Strategy:   Use a mean-skew corrected Gaussian by fitting a Skew-Normal
    Fast mode:  On
    Use linear approximation to log(|Q +c|)? Yes
        Method:  Compute the derivative exact
    Parameters for improved approximations
        Number of points evaluate:   9
        Step length to compute derivatives numerically:  0.000100002
        Stencil to compute derivatives numerically:  5
        Cutoff value to construct local neigborhood:     0.0001
    Log calculations:    On
    Log calculated marginal for the hyperparameters:     On
    Integration strategy:    Automatic (GRID for dim(theta)=1 and 2 and otherwise CCD)
        f0 (CCD only):   1.100000
        dz (GRID only):  0.750000
        Adjust weights (GRID only):  On
        Difference in log-density limit (GRID only):     6.000000
        Skip configurations with (presumed) small density (GRID only):   On
    Gradient is computed using Central difference with step-length 0.010000
    Hessian is computed using Central difference with step-length 0.100000
    Hessian matrix is forced to be a diagonal matrix? [No]
    Compute effective number of parameters? [Yes]
    Perform a Monte Carlo error-test? [No]
    Interpolator [Auto]
    CPO required diff in log-density [3]
    Stupid search mode:
        Status     [On]
        Max iter   [1000]
        Factor     [1.05]
    Numerical integration of hyperparameters:
        Maximum number of function evaluations [100000]
        Relative error ....................... [1e-05]
        Absolute error ....................... [1e-06]
    To stabilise the numerical optimisation:
        Minimum value of the -Hessian [-inf]
    CPO manual calculation[No]
    Laplace-correction is Disabled.

inla_build: check for unused entries in[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/Model.ini]
inla_INLA...
    Strategy = [DEFAULT]
    Size is [9133]
    Chose OpenMP-strategy [LARGE]
    Chose density-strategy [HIGH]
    Size of graph=[9133] constraints=[1]
    Found optimal reordering=[amdbarc] nnz(L)=[67024] and use_global_nodes(user)=[no]
    List of hyperparameters: 
        theta[0] = [Log precision for bymID (idd component)]
        theta[1] = [Log precision for bymID (spatial component)]
Optimise using DEFAULT METHOD
max.logdens= -12212.491312 fn= 1 theta= 4.000000 3.990000  range=[-0.645 3.122]
max.logdens= -12203.547336 fn= 2 theta= 3.990000 4.000000  range=[-0.643 3.128]
max.logdens= -10786.982766 fn= 5 theta= 3.038828 3.724049  range=[-0.805 3.689]
max.logdens= -10784.450551 fn= 6 theta= 3.038828 3.714049  range=[-0.807 3.690]
max.logdens= -10772.356266 fn= 7 theta= 3.028828 3.724049  range=[-0.806 3.693]
max.logdens= -8508.443163 fn= 10 theta= 0.772859 3.073493  range=[-1.574 5.398]
max.logdens= -8507.873932 fn= 11 theta= 0.772859 3.063493  range=[-1.574 5.398]
max.logdens= -8506.273411 fn= 12 theta= 0.762859 3.073493  range=[-1.579 5.400]
max.logdens= -8470.898848 fn= 16 theta= 0.375390 2.959380  range=[-1.808 5.497]
max.logdens= -8470.471804 fn= 17 theta= 0.375390 2.949380  range=[-1.808 5.497]
max.logdens= -8470.367384 fn= 19 theta= 0.385390 2.959380  range=[-1.802 5.494]
Iter=1 |grad|=68.7 |x-x.old|=2.67 |f-f.old|=3.75e+03 
max.logdens= -8427.186006 fn= 21 theta= 0.614126 1.988296  range=[-1.790 5.459]
max.logdens= -8426.615755 fn= 22 theta= 0.604126 1.988296  range=[-1.794 5.461]
max.logdens= -8390.057305 fn= 26 theta= 1.001508 0.412576  range=[-2.029 5.430]
max.logdens= -8389.522477 fn= 27 theta= 1.001508 0.402576  range=[-2.032 5.431]
max.logdens= -8388.645792 fn= 28 theta= 0.991508 0.412576  range=[-2.031 5.432]
max.logdens= -8378.915904 fn= 32 theta= 1.175830 -0.296499  range=[-2.203 5.456]
max.logdens= -8378.544737 fn= 33 theta= 1.175830 -0.306499  range=[-2.206 5.457]
max.logdens= -8377.939108 fn= 34 theta= 1.165830 -0.296499  range=[-2.204 5.457]
max.logdens= -8377.900684 fn= 38 theta= 1.210701 -0.438341  range=[-2.242 5.465]
max.logdens= -8377.677702 fn= 39 theta= 1.210701 -0.448341  range=[-2.245 5.466]
max.logdens= -8377.125364 fn= 40 theta= 1.200701 -0.438341  range=[-2.244 5.467]
Iter=2 |grad|=82 |x-x.old|=2.47 |f-f.old|=93 
max.logdens= -8374.927208 fn= 44 theta= 1.189882 -0.590640  range=[-2.298 5.485]
max.logdens= -8374.443531 fn= 45 theta= 1.179882 -0.590640  range=[-2.299 5.486]
Iter=3 |grad|=40.5 |x-x.old|=0.139 |f-f.old|=3.02 
max.logdens= -8369.345232 fn= 54 theta= 1.063970 -0.482892  range=[-2.281 5.491]
max.logdens= -8369.007640 fn= 56 theta= 1.053970 -0.482892  range=[-2.283 5.493]
max.logdens= -8364.286630 fn= 59 theta= 0.738943 -0.078104  range=[-2.227 5.511]
max.logdens= -8364.072185 fn= 60 theta= 0.738943 -0.088104  range=[-2.230 5.512]
max.logdens= -8363.728975 fn= 62 theta= 0.748943 -0.078104  range=[-2.225 5.510]
max.logdens= -8363.362484 fn= 64 theta= 0.815243 -0.173128  range=[-2.236 5.505]
max.logdens= -8363.279466 fn= 67 theta= 0.825243 -0.173128  range=[-2.234 5.503]
max.logdens= -8363.272041 fn= 68 theta= 0.815243 -0.163128  range=[-2.234 5.504]
Iter=4 |grad|=11.1 |x-x.old|=0.417 |f-f.old|=11.5 
max.logdens= -8363.054352 fn= 70 theta= 0.818023 -0.061950  range=[-2.204 5.497]
max.logdens= -8363.016470 fn= 71 theta= 0.808023 -0.061950  range=[-2.206 5.499]
Iter=5 |grad|=2.59 |x-x.old|=0.0614 |f-f.old|=0.338 
max.logdens= -8363.011411 fn= 81 theta= 0.803432 -0.066380  range=[-2.209 5.500]
max.logdens= -8363.009833 fn= 86 theta= 0.806535 -0.070820  range=[-2.209 5.499]
Iter=6 |grad|=0.118 |x-x.old|=0.0134 |f-f.old|=0.0144 
max.logdens= -8363.003242 fn= 94 theta= 0.806535 -0.071119  range=[-2.209 5.499]
Iter=7 |grad|=0.0979 |x-x.old|=0.000212(pass) |f-f.old|=0.000194(pass) Reached numerical limit!
Number of function evaluations = 107
Compute the Hessian using central differences and step_size[0.1]. Matrix-type [dense]

   405.843789   110.027626
   110.027626    73.194881
Eigenvectors of the Hessian
    0.957608    -0.288076
    0.288076    0.957608
Eigenvalues of the Hessian
    438.943261
    40.095408
StDev/Correlation matrix (scaled inverse Hessian)
     0.064489    -0.638384
                  0.151855
Compute corrected stdev for theta[0]: negative 0.978417  positive 0.984646
Compute corrected stdev for theta[1]: negative 0.911574  positive 0.962673
max.logdens= -8363.009798 fn= 121 theta= 0.806535 -0.071119  range=[-2.209 5.499]
    config  0=[ -0.75  0.00] log(rel.dens)=-0.35, [1] accept, compute, 10.34s
    config  1=[  0.00  0.00] log(rel.dens)=-0.07, [3] accept, compute, 10.68s
    config  2=[  0.00 -0.75] log(rel.dens)=-0.38, [2] accept, compute, 10.71s
    config  3=[  0.75  0.00] log(rel.dens)=-0.31, [0] accept, compute, 10.92s
    config  4=[ -0.75  0.75] log(rel.dens)=-0.63, [3] accept, compute, 10.26s
    config  5=[  0.00  0.75] log(rel.dens)=-0.33, [1] accept, compute, 10.75s
    config  6=[ -0.75 -0.75] log(rel.dens)=-0.64, [2] accept, compute, 10.84s
    config  7=[  0.75 -0.75] log(rel.dens)=-0.53, [0] accept, compute, 10.74s
    config  8=[  0.75  0.75] log(rel.dens)=-0.64, [3] accept, compute, 11.07s
    config  9=[  0.00 -1.50] log(rel.dens)=-1.36, [1] accept, compute, 11.10s
    config 10=[ -1.50  0.00] log(rel.dens)=-1.14, [2] accept, compute, 11.08s
    config 11=[  1.50  0.00] log(rel.dens)=-1.15, [0] accept, compute, 11.07s
    config 12=[ -0.75  1.50] log(rel.dens)=-1.72, [1] accept, compute, 11.30s
    config 13=[  0.75 -1.50] log(rel.dens)=-1.46, [2] accept, compute, 11.45s
    config 14=[  0.00  1.50] log(rel.dens)=-1.22, [3] accept, compute, 12.14s
    config 15=[ -0.75 -1.50] log(rel.dens)=-1.88, [0] accept, compute, 12.03s
    config 16=[  0.75  1.50] log(rel.dens)=-1.47, [1] accept, compute, 13.76s
    config 17=[ -1.50 -0.75] log(rel.dens)=-1.57, [2] accept, compute, 13.62s
    config 18=[  1.50 -0.75] log(rel.dens)=-1.38, [3] accept, compute, 13.52s
    config 19=[ -1.50  0.75] log(rel.dens)=-1.57, [0] accept, compute, 14.18s
    config 20=[  1.50  0.75] log(rel.dens)=-1.48, [1] accept, compute, 16.25s
    config 21=[ -1.50 -1.50] log(rel.dens)=-2.64, [2] accept, compute, 16.38s
    config 22=[  1.50  1.50] log(rel.dens)=-2.33, [3] accept, compute, 16.38s
    config 23=[  1.50 -1.50] log(rel.dens)=-2.16, [0] accept, compute, 15.73s
    config 24=[ -1.50  1.50] log(rel.dens)=-2.77, [1] accept, compute, 12.06s
    config 25=[  2.25  0.00] log(rel.dens)=-2.56, [3] accept, compute, 11.70s
    config 26=[  0.00 -2.25] log(rel.dens)=-3.02, [2] accept, compute, 11.90s
    config 27=[ -2.25  0.00] log(rel.dens)=-2.79, [0] accept, compute, 11.84s
    config 28=[  0.00  2.25] log(rel.dens)=-2.70, [1] accept, compute, 10.91s
    config 29=[ -0.75 -2.25] log(rel.dens)=-3.58, [2] accept, compute, 10.83s
    config 30=[  2.25  0.75] log(rel.dens)=-2.91, [3] accept, compute, 11.25s
    config 31=[  0.75 -2.25] log(rel.dens)=-3.06, [0] accept, compute, 10.58s
    config 32=[ -2.25  0.75] log(rel.dens)=-3.20, [0] accept, compute, 11.06s
    config 33=[  2.25 -0.75] log(rel.dens)=-2.55, [2] accept, compute, 11.37s
    config 34=[ -2.25 -0.75] log(rel.dens)=-2.88, [1] accept, compute, 11.68s
    config 35=[ -0.75  2.25] log(rel.dens)=-3.41, [3] accept, compute, 11.40s
    config 36=[ -2.25 -1.50] log(rel.dens)=-4.09, [2] accept, compute, 10.97s
    config 37=[  0.75  2.25] log(rel.dens)=-2.97, [0] accept, compute, 11.18s
    config 38=[  2.25 -1.50] log(rel.dens)=-3.41, [1] accept, compute, 11.36s
    config 39=[ -1.50 -2.25] log(rel.dens)=-4.65, [3] accept, compute, 11.43s
    config 40=[  2.25  1.50] log(rel.dens)=-3.68, [2] accept, compute, 10.56s
    config 41=[ -1.50  2.25] log(rel.dens)=-4.42, [0] accept, compute, 10.65s
    config 42=[  1.50 -2.25] log(rel.dens)=-3.31, [1] accept, compute, 10.45s
    config 43=[ -2.25  1.50] log(rel.dens)=-4.15, [3] accept, compute, 10.21s
    config 44=[  1.50  2.25] log(rel.dens)=-3.50, [2] accept, compute, 11.32s
    config 45=[  0.00  3.00] log(rel.dens)=-4.70, [0] accept, compute, 11.10s
    config 46=[ -0.75 -3.00] log(rel.dens)=-6.36, reject, 0.25s
    config 47=[  3.00  0.00] log(rel.dens)=-4.46, [1] accept, compute, 11.55s
    config 48=[  0.00 -3.00] log(rel.dens)=-5.55, [3] accept, compute, 11.53s
    config 49=[ -3.00  0.00] log(rel.dens)=-4.50, [2] accept, compute, 11.92s
    config 50=[ -3.00  0.75] log(rel.dens)=-5.02, [0] accept, compute, 11.72s
    config 51=[  3.00  0.75] log(rel.dens)=-4.93, [1] accept, compute, 11.50s
    config 52=[ -0.75  3.00] log(rel.dens)=-5.35, [3] accept, compute, 11.73s
    config 53=[  0.75 -3.00] log(rel.dens)=-5.46, [2] accept, compute, 11.45s
    config 54=[  3.00 -0.75] log(rel.dens)=-4.40, [1] accept, compute, 11.38s
    config 55=[  0.75  3.00] log(rel.dens)=-4.58, [0] accept, compute, 11.52s
    config 56=[ -3.00 -0.75] log(rel.dens)=-4.83, [3] accept, compute, 11.43s
    config 57=[ -2.25 -2.25] log(rel.dens)=-6.21, reject, 0.34s
    config 58=[ -2.25  2.25] log(rel.dens)=-6.20, reject, 0.26s
    config 59=[ -1.50  3.00] log(rel.dens)=-6.70, reject, 0.29s
    config 60=[ -3.00 -1.50] log(rel.dens)=-6.06, reject, 0.32s
    config 61=[  2.25  2.25] log(rel.dens)=-4.83, [2] accept, compute, 11.28s
    config 62=[  2.25 -2.25] log(rel.dens)=-4.22, [1] accept, compute, 11.69s
    config 63=[ -3.00  1.50] log(rel.dens)=-6.34, reject, 0.28s
    config 64=[  1.50 -3.00] log(rel.dens)=-5.31, [0] accept, compute, 11.60s
    config 65=[  3.00  1.50] log(rel.dens)=-5.71, [3] accept, compute, 11.76s
    config 66=[  0.00 -3.75] log(rel.dens)=-9.10, reject, 0.33s
    config 67=[  1.50  3.00] log(rel.dens)=-5.18, [2] accept, compute, 11.66s
    config 68=[  3.00  2.25] log(rel.dens)=-6.87, reject, 0.26s
    config 69=[  2.25  3.00] log(rel.dens)=-6.40, reject, 0.20s
    config 70=[  2.25 -3.00] log(rel.dens)=-5.88, [0] accept, compute, 11.20s
    config 71=[  0.00  3.75] log(rel.dens)=-7.36, reject, 0.22s
    config 72=[  3.75  0.00] log(rel.dens)=-6.96, reject, 0.27s
    config 73=[  3.00 -1.50] log(rel.dens)=-4.67, [1] accept, compute, 11.92s
    config 74=[ -3.75  0.00] log(rel.dens)=-7.03, reject, 0.28s
    config 75=[ -3.75 -0.75] log(rel.dens)=-7.32, reject, 0.20s
    config 76=[  3.00 -3.00] log(rel.dens)=-6.94, reject, 0.13s
    config 77=[  3.00 -2.25] log(rel.dens)=-5.47, [3] accept, compute, 11.25s
Combine the densities with relative weights:
    config  0/64=[ -0.75  0.00] weight = 0.756 adjusted weight = 0.733  neff = 2084.27
    config  1/64=[  0.00  0.00] weight = 1.000 adjusted weight = 0.957  neff = 2070.66
    config  2/64=[  0.00 -0.75] weight = 0.735 adjusted weight = 0.712  neff = 2072.02
    config  3/64=[  0.75  0.00] weight = 0.787 adjusted weight = 0.763  neff = 2056.92
    config  4/64=[ -0.75  0.75] weight = 0.574 adjusted weight = 0.564  neff = 2084.89
    config  5/64=[  0.00  0.75] weight = 0.772 adjusted weight = 0.748  neff = 2071.00
    config  6/64=[ -0.75 -0.75] weight = 0.570 adjusted weight = 0.559  neff = 2085.26
    config  7/64=[  0.75 -0.75] weight = 0.634 adjusted weight = 0.623  neff = 2058.59
    config  8/64=[  0.75  0.75] weight = 0.567 adjusted weight = 0.557  neff = 2057.03
    config  9/64=[  0.00 -1.50] weight = 0.277 adjusted weight = 0.279  neff = 2075.26
    config 10/64=[ -1.50  0.00] weight = 0.344 adjusted weight = 0.347  neff = 2097.74
    config 11/64=[  1.50  0.00] weight = 0.342 adjusted weight = 0.345  neff = 2043.15
    config 12/64=[ -0.75  1.50] weight = 0.193 adjusted weight = 0.197  neff = 2087.27
    config 13/64=[  0.75 -1.50] weight = 0.249 adjusted weight = 0.254  neff = 2062.25
    config 14/64=[  0.00  1.50] weight = 0.318 adjusted weight = 0.320  neff = 2073.02
    config 15/64=[ -0.75 -1.50] weight = 0.164 adjusted weight = 0.167  neff = 2088.29
    config 16/64=[  0.75  1.50] weight = 0.247 adjusted weight = 0.252  neff = 2058.81
    config 17/64=[ -1.50 -0.75] weight = 0.224 adjusted weight = 0.228  neff = 2098.54
    config 18/64=[  1.50 -0.75] weight = 0.272 adjusted weight = 0.277  neff = 2045.23
    config 19/64=[ -1.50  0.75] weight = 0.223 adjusted weight = 0.227  neff = 2098.74
    config 20/64=[  1.50  0.75] weight = 0.246 adjusted weight = 0.251  neff = 2042.94
    config 21/64=[ -1.50 -1.50] weight = 0.077 adjusted weight = 0.081  neff = 2101.02
    config 22/64=[  1.50  1.50] weight = 0.105 adjusted weight = 0.111  neff = 2044.52
    config 23/64=[  1.50 -1.50] weight = 0.124 adjusted weight = 0.132  neff = 2049.25
    config 24/64=[ -1.50  1.50] weight = 0.067 adjusted weight = 0.071  neff = 2101.34
    config 25/64=[  2.25  0.00] weight = 0.084 adjusted weight = 0.090  neff = 2029.31
    config 26/64=[  0.00 -2.25] weight = 0.052 adjusted weight = 0.056  neff = 2080.39
    config 27/64=[ -2.25  0.00] weight = 0.066 adjusted weight = 0.071  neff = 2111.36
    config 28/64=[  0.00  2.25] weight = 0.072 adjusted weight = 0.077  neff = 2076.60
    config 29/64=[ -0.75 -2.25] weight = 0.030 adjusted weight = 0.032  neff = 2092.93
    config 30/64=[  2.25  0.75] weight = 0.059 adjusted weight = 0.064  neff = 2028.78
    config 31/64=[  0.75 -2.25] weight = 0.050 adjusted weight = 0.055  neff = 2067.88
    config 32/64=[ -2.25  0.75] weight = 0.044 adjusted weight = 0.048  neff = 2112.55
    config 33/64=[  2.25 -0.75] weight = 0.084 adjusted weight = 0.091  neff = 2031.64
    config 34/64=[ -2.25 -0.75] weight = 0.060 adjusted weight = 0.065  neff = 2111.62
    config 35/64=[ -0.75  2.25] weight = 0.036 adjusted weight = 0.039  neff = 2091.08
    config 36/64=[ -2.25 -1.50] weight = 0.018 adjusted weight = 0.020  neff = 2113.82
    config 37/64=[  0.75  2.25] weight = 0.055 adjusted weight = 0.060  neff = 2062.29
    config 38/64=[  2.25 -1.50] weight = 0.035 adjusted weight = 0.040  neff = 2036.24
    config 39/64=[ -1.50 -2.25] weight = 0.010 adjusted weight = 0.012  neff = 2105.43
    config 40/64=[  2.25  1.50] weight = 0.027 adjusted weight = 0.031  neff = 2030.01
    config 41/64=[ -1.50  2.25] weight = 0.013 adjusted weight = 0.015  neff = 2105.22
    config 42/64=[  1.50 -2.25] weight = 0.039 adjusted weight = 0.044  neff = 2055.10
    config 43/64=[ -2.25  1.50] weight = 0.017 adjusted weight = 0.019  neff = 2115.10
    config 44/64=[  1.50  2.25] weight = 0.032 adjusted weight = 0.036  neff = 2047.56
    config 45/64=[  0.00  3.00] weight = 0.010 adjusted weight = 0.011  neff = 2081.53
    config 46/64=[  3.00  0.00] weight = 0.012 adjusted weight = 0.014  neff = 2015.35
    config 47/64=[  0.00 -3.00] weight = 0.004 adjusted weight = 0.005  neff = 2087.57
    config 48/64=[ -3.00  0.00] weight = 0.012 adjusted weight = 0.014  neff = 2124.52
    config 49/64=[ -3.00  0.75] weight = 0.007 adjusted weight = 0.008  neff = 2125.97
    config 50/64=[  3.00  0.75] weight = 0.008 adjusted weight = 0.009  neff = 2014.54
    config 51/64=[ -0.75  3.00] weight = 0.005 adjusted weight = 0.006  neff = 2096.00
    config 52/64=[  0.75 -3.00] weight = 0.005 adjusted weight = 0.005  neff = 2075.58
    config 53/64=[  3.00 -0.75] weight = 0.013 adjusted weight = 0.016  neff = 2018.10
    config 54/64=[  0.75  3.00] weight = 0.011 adjusted weight = 0.013  neff = 2066.85
    config 55/64=[ -3.00 -0.75] weight = 0.009 adjusted weight = 0.010  neff = 2124.68
    config 56/64=[  2.25  2.25] weight = 0.009 adjusted weight = 0.010  neff = 2032.88
    config 57/64=[  2.25 -2.25] weight = 0.016 adjusted weight = 0.019  neff = 2042.42
    config 58/64=[  1.50 -3.00] weight = 0.005 adjusted weight = 0.007  neff = 2063.13
    config 59/64=[  3.00  1.50] weight = 0.004 adjusted weight = 0.004  neff = 2015.49
    config 60/64=[  1.50  3.00] weight = 0.006 adjusted weight = 0.007  neff = 2052.12
    config 61/64=[  2.25 -3.00] weight = 0.003 adjusted weight = 0.004  neff = 2050.86
    config 62/64=[  3.00 -1.50] weight = 0.010 adjusted weight = 0.012  neff = 2022.78
    config 63/64=[  3.00 -2.25] weight = 0.005 adjusted weight = 0.006  neff = 2029.58
Done.
Expected effective number of parameters: 2070.494(18.418),  eqv.#replicates: 1.470
DIC:
    Mean of Deviance................. 12253.7
    Deviance at Mean................. 10220.4
    Effective number of parameters... 2033.32
    DIC.............................. 14287
Marginal likelihood: Integration -8365.796155 Gaussian-approx -8366.059737
Compute the marginal for each of the 2 hyperparameters
Interpolation method: Auto
    Compute the marginal for theta[0] to theta[1] using numerical integration...
    Compute the marginal for theta[0] to theta[1] using numerical integration... Done.
Compute the marginal for the hyperparameters... done.
Store results in directory[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/results.files]

Wall-clock time used on [/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0fa178e57/Model.ini]
    Preparations    :   0.097 seconds
    Approx inference: 209.341 seconds [0.1|0.0|4.1|90.2|5.5]%
    Output          :   0.583 seconds
    ---------------------------------
    Total           : 210.021 seconds

breaks <- c(0,0.1,0.25,0.5,0.75,1,1.5,2.5,3,5,202)
results2 <- data.frame(bymID=BYM_data$bymID, CD_GEOCODI=BYM_data$CD_GEOCODI, fit_SMR = model_bym_null$summary.fitted.values$mean, CI95_lower = model_bym_null$summary.fitted.values$`0.025quant`, CI95_upper=model_bym_null$summary.fitted.values$`0.975quant`)
CT_shp_gg_SMR_smth <- CT_shp_gg_SMR %>% left_join(results2, by=c("CD_GEOCODI")) %>% mutate(fit_cut=cut(fit_SMR, breaks=breaks, labels=(c("[0,0.1]","(0.1,0.25]","(0.25,0.5]","(0.5,0.75]","(0.75,1]","(1,1.5]","(1.5,2.5]","(2.5,3]","(3,5]", ">5")), include.lowest=TRUE))

Column `CD_GEOCODI` joining character vector and factor, coercing into character vector

plot_fort_maps2(CT_shp_gg_SMR_smth, "fit_cut","BYM smoothed SMR", "Aggregate BYM smoothed SMR for 2001-17 by CT") + theme(plot.title = element_text(size=10), legend.position = "right")

set.seed(2014)
plot(1,1, type="n", xlim=c(550,650), ylim=c(0,10),
  main= "Confidence intervals of the SMR",
  xlab="County", ylab="Relative Risk", xaxt="n")
abline(h=1, lty=2)

for(i in 500:650){
  if(!is.na(results2$fit_SMR[i])){
        if(results2$CI95_lower[i]>1 ) {
            sig.col <- brewer.pal(4, "Reds")[4]
            col <- sig.col
            lty <- 2
            #text(i, SMR_data$CI95_upper[i]+.31,
                #srt=90, col=sig.col, cex=.85)
        } else {
            col <- "black"
            lty <- 1
        }
        lines(c(i,i), c(results2$CI95_lower[i],results2$CI95_upper[i]), col=col, lty=lty)
        points(x=i, y=results2$fit_SMR[i], pch=18, col=col)
  }
}

covariates <- read_csv("Census_data/census_covariates_Fortaleza_01_03_19.csv", 
    col_types = cols(Cod_setor = col_character()))

Calculate LII

covariates <- covariates %>% mutate(Total_no_HH_in_CT=replace(Total_no_HH_in_CT, is.na(Total_no_HH_in_CT), 0), Total_HH_inc_in_CT=replace(Total_HH_inc_in_CT, is.na(Total_HH_inc_in_CT), 0), Mean_HH_inc=replace(Mean_HH_inc, is.na(Mean_HH_inc), 0))
                                    
                                    
covariates$LII <- NA
for (i in 1:3044){
  CT_Code <- CT_shp@data$CD_GEOCODI[i]
  neighbors_codes <- CT_shp@data$CD_GEOCODI[CT_wm[[i]]]
  total_nb_inc <- sum(covariates[(covariates$Cod_setor %in% neighbors_codes),]$Total_HH_inc_in_CT)
  total_nb_hh <- sum(covariates[(covariates$Cod_setor %in% neighbors_codes),]$Total_no_HH_in_CT)
  Mean_nb_inc <- total_nb_inc / total_nb_hh
  LII <- Mean_nb_inc / covariates[(covariates$Cod_setor)==CT_Code,]$Mean_HH_inc
  covariates[(covariates$Cod_setor==CT_Code),]$LII <- LII
}
covariates$LII[covariates$LII==Inf] <- NA 
covariates$log_LII <- log(covariates$LII)

BYM_data_covar <- BYM_data %>% left_join(covariates, by=c("CD_GEOCODI"="Cod_setor")) %>% mutate(log_mean_HH_inc=log(Mean_HH_inc)) %>% arrange(CD_GEOCODI) %>% mutate(bymID=1:3044)
BYM_data_covar <- BYM_data_covar %>% mutate(log_mean_HH_inc=replace(log_mean_HH_inc, log_mean_HH_inc==-Inf | is.na(log_mean_HH_inc), 0), log_LII=replace(log_LII, log_LII==-Inf | is.na(log_LII), 0), Perc_Wtr_Spply_Ntwrk=replace(Perc_Wtr_Spply_Ntwrk, is.na(Perc_Wtr_Spply_Ntwrk), 0), Perc_branca=replace(Perc_branca, is.na(Perc_branca), 0), Perc_Garbage_Col_Serv=replace(Perc_Garbage_Col_Serv, is.na(Perc_Garbage_Col_Serv), 0), Perc_PPH_Elec=replace(Perc_PPH_Elec, is.na(Perc_PPH_Elec), 0), Lit_rate=replace(Lit_rate, is.na(Lit_rate), 0), ICE=replace(ICE, is.na(ICE), 0)) 
BYM_data_covar <- BYM_data_covar %>% mutate(ICE_quant=cut(ICE, breaks=quantile(BYM_data_covar$ICE, probs=c(seq(0,1,0.25),1)[1:5]), include.lowest=TRUE))

formula_bym_7 <- y ~ 1 + f(bymID, model="bym", graph=CT_adj) + log_inc_quant + ICE_quant + log_LII_quant + Lit_rate_demean + Perc_branca_demean
model_bym_7 <- inla(formula_bym_7, family="poisson", data=BYM_data_covar, E=E, control.predictor=list(compute=TRUE), control.compute = list(dic = TRUE), verbose = TRUE)

    hgid: 29c6a7f1b1ff  date: Thu Jun 15 19:50:23 2017 +0800
Report bugs to <help@r-inla.org>
Processing file [/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/Model.ini] max_threads=[4]
inla_build...
    number of sections=[19]
    parse section=[0] name=[INLA.libR] type=[LIBR]
    inla_parse_libR...
        section[INLA.libR]
            R_HOME=[/Library/Frameworks/R.framework/Resources]
    parse section=[18] name=[INLA.Expert] type=[EXPERT]
    inla_parse_expert...
        section[INLA.Expert]
            disable.gaussian.check=[0]
            cpo.manual=[0]
            jp.Rfile=[(null)]
            jp.RData=NULL
            jp.func=[(null)]
    parse section=[1] name=[INLA.Model] type=[PROBLEM]
    inla_parse_problem...
        name=[INLA.Model]
        openmp.strategy=[default]
    store results in directory=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/results.files]
        output:
            cpo=[0]
            po=[0]
            dic=[1]
            kld=[1]
            mlik=[1]
            q=[0]
            graph=[0]
            gdensity=[0]
            hyperparameters=[1]
            summary=[1]
            return.marginals=[1]
            nquantiles=[3]  [ 0.025 0.5 0.975 ]
            ncdf=[0]  [ ]
    parse section=[3] name=[Predictor] type=[PREDICTOR]
    inla_parse_predictor ...
        section=[Predictor]
        dir=[predictor]
        PRIOR->name=[loggamma]
        hyperid=[53001|Predictor]
        PRIOR->from_theta=[function (x) <<NEWLINE>>exp(x)]
        PRIOR->to_theta = [function (x) <<NEWLINE>>log(x)]
        PRIOR->PARAMETERS=[1, 1e-05]
        initialise log_precision[12]
        fixed=[1]
        user.scale=[1]
        n=[3044]
        m=[0]
        ndata=[3044]
        compute=[1]
        read offsets from file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1b230a16]
        read n=[6088] entries from file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1b230a16]
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1b230a16] 0/3044  (idx,y) = (0, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1b230a16] 1/3044  (idx,y) = (1, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1b230a16] 2/3044  (idx,y) = (2, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1b230a16] 3/3044  (idx,y) = (3, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1b230a16] 4/3044  (idx,y) = (4, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1b230a16] 5/3044  (idx,y) = (5, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1b230a16] 6/3044  (idx,y) = (6, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1b230a16] 7/3044  (idx,y) = (7, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1b230a16] 8/3044  (idx,y) = (8, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1b230a16] 9/3044  (idx,y) = (9, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1b230a16] 10/3044  (idx,y) = (10, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1b230a16] 11/3044  (idx,y) = (11, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1b230a16] 12/3044  (idx,y) = (12, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1b230a16] 13/3044  (idx,y) = (13, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1b230a16] 14/3044  (idx,y) = (14, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1b230a16] 15/3044  (idx,y) = (15, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1b230a16] 16/3044  (idx,y) = (16, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1b230a16] 17/3044  (idx,y) = (17, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1b230a16] 18/3044  (idx,y) = (18, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1b230a16] 19/3044  (idx,y) = (19, 0)
        Aext=[(null)]
        AextPrecision=[1e+08]
        output:
            summary=[1]
            return.marginals=[1]
            nquantiles=[3]  [ 0.025 0.5 0.975 ]
            ncdf=[0]  [ ]
    parse section=[2] name=[INLA.Data1] type=[DATA]
    inla_parse_data [section 1]...
        tag=[INLA.Data1]
        family=[POISSON]
        likelihood=[POISSON]
        file->name=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f40eefc65]
        file->name=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f9fc6c31]
        read n=[9132] entries from file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f40eefc65]
            0/3044  (idx,a,y,d) = (0, 14.827, 12, 1)
            1/3044  (idx,a,y,d) = (1, 4.88122, 4, 1)
            2/3044  (idx,a,y,d) = (2, 9.75508, 31, 1)
            3/3044  (idx,a,y,d) = (3, 10.764, 10, 1)
            4/3044  (idx,a,y,d) = (4, 7.50958, 5, 1)
            5/3044  (idx,a,y,d) = (5, 7.69529, 9, 1)
            6/3044  (idx,a,y,d) = (6, 4.62971, 7, 1)
            7/3044  (idx,a,y,d) = (7, 6.07998, 11, 1)
            8/3044  (idx,a,y,d) = (8, 5.20853, 6, 1)
            9/3044  (idx,a,y,d) = (9, 9.1703, 1, 1)
            10/3044  (idx,a,y,d) = (10, 5.07622, 5, 1)
            11/3044  (idx,a,y,d) = (11, 5.27241, 1, 1)
            12/3044  (idx,a,y,d) = (12, 2.71774, 4, 1)
            13/3044  (idx,a,y,d) = (13, 3.94485, 1, 1)
            14/3044  (idx,a,y,d) = (14, 6.43779, 3, 1)
            15/3044  (idx,a,y,d) = (15, 5.35615, 4, 1)
            16/3044  (idx,a,y,d) = (16, 8.77675, 2, 1)
            17/3044  (idx,a,y,d) = (17, 5.14462, 2, 1)
            18/3044  (idx,a,y,d) = (18, 5.87517, 1, 1)
            19/3044  (idx,a,y,d) = (19, 5.50689, 3, 1)
        likelihood.variant=[0]
        Link model   [LOG]
        Link order   [-1]
        Link variant [-1]
        Link ntheta  [0]
        mix.use[0]
    parse section=[16] name=[bymID] type=[FFIELD]
    inla_parse_ffield...
        section=[bymID]
        dir=[random.effect00000001]
        model=[bym]
        PRIOR0->name=[loggamma]
        hyperid=[10001|bymID]
        PRIOR0->from_theta=[function (x) <<NEWLINE>>exp(x)]
        PRIOR0->to_theta = [function (x) <<NEWLINE>>log(x)]
        PRIOR0->PARAMETERS0=[1, 0.0005]
        PRIOR1->name=[loggamma]
        hyperid=[10002|bymID]
        PRIOR1->from_theta=[function (x) <<NEWLINE>>exp(x)]
        PRIOR1->to_theta = [function (x) <<NEWLINE>>log(x)]
        PRIOR1->PARAMETERS1=[1, 0.0005]
        correct=[-1]
        constr=[0]
        diagonal=[1.01511e-05]
        id.names=<not present>
        compute=[1]
        nrep=[1]
        ngroup=[1]
        read covariates from file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7bc7abcd]
        read n=[6088] entries from file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7bc7abcd]
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7bc7abcd] 0/3044  (idx,y) = (0, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7bc7abcd] 1/3044  (idx,y) = (1, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7bc7abcd] 2/3044  (idx,y) = (2, 2)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7bc7abcd] 3/3044  (idx,y) = (3, 3)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7bc7abcd] 4/3044  (idx,y) = (4, 4)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7bc7abcd] 5/3044  (idx,y) = (5, 5)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7bc7abcd] 6/3044  (idx,y) = (6, 6)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7bc7abcd] 7/3044  (idx,y) = (7, 7)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7bc7abcd] 8/3044  (idx,y) = (8, 8)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7bc7abcd] 9/3044  (idx,y) = (9, 9)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7bc7abcd] 10/3044  (idx,y) = (10, 10)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7bc7abcd] 11/3044  (idx,y) = (11, 11)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7bc7abcd] 12/3044  (idx,y) = (12, 12)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7bc7abcd] 13/3044  (idx,y) = (13, 13)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7bc7abcd] 14/3044  (idx,y) = (14, 14)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7bc7abcd] 15/3044  (idx,y) = (15, 15)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7bc7abcd] 16/3044  (idx,y) = (16, 16)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7bc7abcd] 17/3044  (idx,y) = (17, 17)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7bc7abcd] 18/3044  (idx,y) = (18, 18)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7bc7abcd] 19/3044  (idx,y) = (19, 19)
        read graph from file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f20c0bc3d]
        file for locations=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f2a69cfc6]
            nlocations=[3044]
            locations[0]=[1]
            locations[1]=[2]
            locations[2]=[3]
            locations[3]=[4]
            locations[4]=[5]
            locations[5]=[6]
            locations[6]=[7]
            locations[7]=[8]
            locations[8]=[9]
            locations[9]=[10]
            locations[10]=[11]
            locations[11]=[12]
            locations[12]=[13]
            locations[13]=[14]
            locations[14]=[15]
            locations[15]=[16]
            locations[16]=[17]
            locations[17]=[18]
            locations[18]=[19]
            locations[19]=[20]
        initialise log_precision (iid component)[4]
        fixed=[0]
        initialise log_precision (spatial component)[4]
        fixed=[0]
        adjust.for.con.comp[1]
        scale.model[0]
        read extra constraint from file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f71e05f37]
        Constraint[0]
            A[3044] = 1.000000
            A[3045] = 1.000000
            A[3046] = 1.000000
            A[3047] = 1.000000
            A[3048] = 1.000000
            A[3049] = 1.000000
            A[3050] = 1.000000
            A[3051] = 1.000000
            A[3052] = 1.000000
            A[3053] = 1.000000
            A[3054] = 1.000000
            A[3055] = 1.000000
            A[3056] = 1.000000
            A[3057] = 1.000000
            A[3058] = 1.000000
            A[3059] = 1.000000
            A[3060] = 1.000000
            A[3061] = 1.000000
            A[3062] = 1.000000
            A[3063] = 1.000000
            A[3064] = 1.000000
            e[0] = 0.000000
        rank-deficiency is *defined* [1]
        output:
            summary=[1]
            return.marginals=[1]
            nquantiles=[3]  [ 0.025 0.5 0.975 ]
            ncdf=[0]  [ ]
    section=[4] name=[(Intercept)] type=[LINEAR]
    inla_parse_linear...
        section[(Intercept)]
        dir=[fixed.effect00000001]
        file for covariates=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f196b3845]
        read n=[6088] entries from file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f196b3845]
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f196b3845] 0/3044  (idx,y) = (0, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f196b3845] 1/3044  (idx,y) = (1, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f196b3845] 2/3044  (idx,y) = (2, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f196b3845] 3/3044  (idx,y) = (3, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f196b3845] 4/3044  (idx,y) = (4, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f196b3845] 5/3044  (idx,y) = (5, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f196b3845] 6/3044  (idx,y) = (6, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f196b3845] 7/3044  (idx,y) = (7, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f196b3845] 8/3044  (idx,y) = (8, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f196b3845] 9/3044  (idx,y) = (9, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f196b3845] 10/3044  (idx,y) = (10, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f196b3845] 11/3044  (idx,y) = (11, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f196b3845] 12/3044  (idx,y) = (12, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f196b3845] 13/3044  (idx,y) = (13, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f196b3845] 14/3044  (idx,y) = (14, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f196b3845] 15/3044  (idx,y) = (15, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f196b3845] 16/3044  (idx,y) = (16, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f196b3845] 17/3044  (idx,y) = (17, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f196b3845] 18/3044  (idx,y) = (18, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f196b3845] 19/3044  (idx,y) = (19, 1)
        prior mean=[0]
        prior precision=[0]
        compute=[1]
        output:
            summary=[1]
            return.marginals=[1]
            nquantiles=[3]  [ 0.025 0.5 0.975 ]
            ncdf=[0]  [ ]
    section=[5] name=[log_inc_quant(6.95,7.3] type=[LINEAR]
    inla_parse_linear...
        section[log_inc_quant(6.95,7.3]
        dir=[fixed.effect00000002]
        file for covariates=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4e3b470c]
        read n=[6088] entries from file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4e3b470c]
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4e3b470c] 0/3044  (idx,y) = (0, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4e3b470c] 1/3044  (idx,y) = (1, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4e3b470c] 2/3044  (idx,y) = (2, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4e3b470c] 3/3044  (idx,y) = (3, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4e3b470c] 4/3044  (idx,y) = (4, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4e3b470c] 5/3044  (idx,y) = (5, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4e3b470c] 6/3044  (idx,y) = (6, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4e3b470c] 7/3044  (idx,y) = (7, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4e3b470c] 8/3044  (idx,y) = (8, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4e3b470c] 9/3044  (idx,y) = (9, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4e3b470c] 10/3044  (idx,y) = (10, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4e3b470c] 11/3044  (idx,y) = (11, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4e3b470c] 12/3044  (idx,y) = (12, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4e3b470c] 13/3044  (idx,y) = (13, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4e3b470c] 14/3044  (idx,y) = (14, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4e3b470c] 15/3044  (idx,y) = (15, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4e3b470c] 16/3044  (idx,y) = (16, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4e3b470c] 17/3044  (idx,y) = (17, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4e3b470c] 18/3044  (idx,y) = (18, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4e3b470c] 19/3044  (idx,y) = (19, 0)
        prior mean=[0]
        prior precision=[0.001]
        compute=[1]
        output:
            summary=[1]
            return.marginals=[1]
            nquantiles=[3]  [ 0.025 0.5 0.975 ]
            ncdf=[0]  [ ]
    section=[6] name=[log_inc_quant(7.3,7.81] type=[LINEAR]
    inla_parse_linear...
        section[log_inc_quant(7.3,7.81]
        dir=[fixed.effect00000003]
        file for covariates=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f15b58cf4]
        read n=[6088] entries from file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f15b58cf4]
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f15b58cf4] 0/3044  (idx,y) = (0, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f15b58cf4] 1/3044  (idx,y) = (1, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f15b58cf4] 2/3044  (idx,y) = (2, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f15b58cf4] 3/3044  (idx,y) = (3, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f15b58cf4] 4/3044  (idx,y) = (4, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f15b58cf4] 5/3044  (idx,y) = (5, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f15b58cf4] 6/3044  (idx,y) = (6, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f15b58cf4] 7/3044  (idx,y) = (7, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f15b58cf4] 8/3044  (idx,y) = (8, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f15b58cf4] 9/3044  (idx,y) = (9, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f15b58cf4] 10/3044  (idx,y) = (10, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f15b58cf4] 11/3044  (idx,y) = (11, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f15b58cf4] 12/3044  (idx,y) = (12, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f15b58cf4] 13/3044  (idx,y) = (13, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f15b58cf4] 14/3044  (idx,y) = (14, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f15b58cf4] 15/3044  (idx,y) = (15, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f15b58cf4] 16/3044  (idx,y) = (16, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f15b58cf4] 17/3044  (idx,y) = (17, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f15b58cf4] 18/3044  (idx,y) = (18, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f15b58cf4] 19/3044  (idx,y) = (19, 1)
        prior mean=[0]
        prior precision=[0.001]
        compute=[1]
        output:
            summary=[1]
            return.marginals=[1]
            nquantiles=[3]  [ 0.025 0.5 0.975 ]
            ncdf=[0]  [ ]
    section=[7] name=[log_inc_quant(7.81,9.99] type=[LINEAR]
    inla_parse_linear...
        section[log_inc_quant(7.81,9.99]
        dir=[fixed.effect00000004]
        file for covariates=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4238f24e]
        read n=[6088] entries from file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4238f24e]
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4238f24e] 0/3044  (idx,y) = (0, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4238f24e] 1/3044  (idx,y) = (1, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4238f24e] 2/3044  (idx,y) = (2, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4238f24e] 3/3044  (idx,y) = (3, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4238f24e] 4/3044  (idx,y) = (4, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4238f24e] 5/3044  (idx,y) = (5, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4238f24e] 6/3044  (idx,y) = (6, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4238f24e] 7/3044  (idx,y) = (7, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4238f24e] 8/3044  (idx,y) = (8, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4238f24e] 9/3044  (idx,y) = (9, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4238f24e] 10/3044  (idx,y) = (10, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4238f24e] 11/3044  (idx,y) = (11, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4238f24e] 12/3044  (idx,y) = (12, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4238f24e] 13/3044  (idx,y) = (13, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4238f24e] 14/3044  (idx,y) = (14, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4238f24e] 15/3044  (idx,y) = (15, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4238f24e] 16/3044  (idx,y) = (16, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4238f24e] 17/3044  (idx,y) = (17, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4238f24e] 18/3044  (idx,y) = (18, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f4238f24e] 19/3044  (idx,y) = (19, 0)
        prior mean=[0]
        prior precision=[0.001]
        compute=[1]
        output:
            summary=[1]
            return.marginals=[1]
            nquantiles=[3]  [ 0.025 0.5 0.975 ]
            ncdf=[0]  [ ]
    section=[8] name=[ICE_quant(-0.185,-0.0955] type=[LINEAR]
    inla_parse_linear...
        section[ICE_quant(-0.185,-0.0955]
        dir=[fixed.effect00000005]
        file for covariates=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f28ac00d9]
        read n=[6088] entries from file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f28ac00d9]
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f28ac00d9] 0/3044  (idx,y) = (0, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f28ac00d9] 1/3044  (idx,y) = (1, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f28ac00d9] 2/3044  (idx,y) = (2, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f28ac00d9] 3/3044  (idx,y) = (3, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f28ac00d9] 4/3044  (idx,y) = (4, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f28ac00d9] 5/3044  (idx,y) = (5, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f28ac00d9] 6/3044  (idx,y) = (6, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f28ac00d9] 7/3044  (idx,y) = (7, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f28ac00d9] 8/3044  (idx,y) = (8, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f28ac00d9] 9/3044  (idx,y) = (9, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f28ac00d9] 10/3044  (idx,y) = (10, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f28ac00d9] 11/3044  (idx,y) = (11, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f28ac00d9] 12/3044  (idx,y) = (12, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f28ac00d9] 13/3044  (idx,y) = (13, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f28ac00d9] 14/3044  (idx,y) = (14, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f28ac00d9] 15/3044  (idx,y) = (15, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f28ac00d9] 16/3044  (idx,y) = (16, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f28ac00d9] 17/3044  (idx,y) = (17, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f28ac00d9] 18/3044  (idx,y) = (18, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f28ac00d9] 19/3044  (idx,y) = (19, 0)
        prior mean=[0]
        prior precision=[0.001]
        compute=[1]
        output:
            summary=[1]
            return.marginals=[1]
            nquantiles=[3]  [ 0.025 0.5 0.975 ]
            ncdf=[0]  [ ]
    section=[9] name=[ICE_quant(-0.0955,-0.00566] type=[LINEAR]
    inla_parse_linear...
        section[ICE_quant(-0.0955,-0.00566]
        dir=[fixed.effect00000006]
        file for covariates=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f346bbb6b]
        read n=[6088] entries from file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f346bbb6b]
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f346bbb6b] 0/3044  (idx,y) = (0, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f346bbb6b] 1/3044  (idx,y) = (1, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f346bbb6b] 2/3044  (idx,y) = (2, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f346bbb6b] 3/3044  (idx,y) = (3, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f346bbb6b] 4/3044  (idx,y) = (4, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f346bbb6b] 5/3044  (idx,y) = (5, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f346bbb6b] 6/3044  (idx,y) = (6, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f346bbb6b] 7/3044  (idx,y) = (7, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f346bbb6b] 8/3044  (idx,y) = (8, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f346bbb6b] 9/3044  (idx,y) = (9, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f346bbb6b] 10/3044  (idx,y) = (10, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f346bbb6b] 11/3044  (idx,y) = (11, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f346bbb6b] 12/3044  (idx,y) = (12, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f346bbb6b] 13/3044  (idx,y) = (13, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f346bbb6b] 14/3044  (idx,y) = (14, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f346bbb6b] 15/3044  (idx,y) = (15, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f346bbb6b] 16/3044  (idx,y) = (16, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f346bbb6b] 17/3044  (idx,y) = (17, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f346bbb6b] 18/3044  (idx,y) = (18, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f346bbb6b] 19/3044  (idx,y) = (19, 1)
        prior mean=[0]
        prior precision=[0.001]
        compute=[1]
        output:
            summary=[1]
            return.marginals=[1]
            nquantiles=[3]  [ 0.025 0.5 0.975 ]
            ncdf=[0]  [ ]
    section=[10] name=[ICE_quant(-0.00566,0.888] type=[LINEAR]
    inla_parse_linear...
        section[ICE_quant(-0.00566,0.888]
        dir=[fixed.effect00000007]
        file for covariates=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0fcdd88b0]
        read n=[6088] entries from file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0fcdd88b0]
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0fcdd88b0] 0/3044  (idx,y) = (0, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0fcdd88b0] 1/3044  (idx,y) = (1, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0fcdd88b0] 2/3044  (idx,y) = (2, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0fcdd88b0] 3/3044  (idx,y) = (3, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0fcdd88b0] 4/3044  (idx,y) = (4, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0fcdd88b0] 5/3044  (idx,y) = (5, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0fcdd88b0] 6/3044  (idx,y) = (6, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0fcdd88b0] 7/3044  (idx,y) = (7, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0fcdd88b0] 8/3044  (idx,y) = (8, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0fcdd88b0] 9/3044  (idx,y) = (9, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0fcdd88b0] 10/3044  (idx,y) = (10, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0fcdd88b0] 11/3044  (idx,y) = (11, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0fcdd88b0] 12/3044  (idx,y) = (12, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0fcdd88b0] 13/3044  (idx,y) = (13, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0fcdd88b0] 14/3044  (idx,y) = (14, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0fcdd88b0] 15/3044  (idx,y) = (15, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0fcdd88b0] 16/3044  (idx,y) = (16, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0fcdd88b0] 17/3044  (idx,y) = (17, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0fcdd88b0] 18/3044  (idx,y) = (18, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0fcdd88b0] 19/3044  (idx,y) = (19, 0)
        prior mean=[0]
        prior precision=[0.001]
        compute=[1]
        output:
            summary=[1]
            return.marginals=[1]
            nquantiles=[3]  [ 0.025 0.5 0.975 ]
            ncdf=[0]  [ ]
    section=[11] name=[log_LII_quant(-0.169,0.07] type=[LINEAR]
    inla_parse_linear...
        section[log_LII_quant(-0.169,0.07]
        dir=[fixed.effect00000008]
        file for covariates=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f2438e169]
        read n=[6088] entries from file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f2438e169]
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f2438e169] 0/3044  (idx,y) = (0, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f2438e169] 1/3044  (idx,y) = (1, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f2438e169] 2/3044  (idx,y) = (2, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f2438e169] 3/3044  (idx,y) = (3, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f2438e169] 4/3044  (idx,y) = (4, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f2438e169] 5/3044  (idx,y) = (5, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f2438e169] 6/3044  (idx,y) = (6, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f2438e169] 7/3044  (idx,y) = (7, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f2438e169] 8/3044  (idx,y) = (8, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f2438e169] 9/3044  (idx,y) = (9, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f2438e169] 10/3044  (idx,y) = (10, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f2438e169] 11/3044  (idx,y) = (11, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f2438e169] 12/3044  (idx,y) = (12, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f2438e169] 13/3044  (idx,y) = (13, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f2438e169] 14/3044  (idx,y) = (14, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f2438e169] 15/3044  (idx,y) = (15, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f2438e169] 16/3044  (idx,y) = (16, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f2438e169] 17/3044  (idx,y) = (17, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f2438e169] 18/3044  (idx,y) = (18, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f2438e169] 19/3044  (idx,y) = (19, 0)
        prior mean=[0]
        prior precision=[0.001]
        compute=[1]
        output:
            summary=[1]
            return.marginals=[1]
            nquantiles=[3]  [ 0.025 0.5 0.975 ]
            ncdf=[0]  [ ]
    section=[12] name=[log_LII_quant(0.07,0.337] type=[LINEAR]
    inla_parse_linear...
        section[log_LII_quant(0.07,0.337]
        dir=[fixed.effect00000009]
        file for covariates=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1256c713]
        read n=[6088] entries from file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1256c713]
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1256c713] 0/3044  (idx,y) = (0, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1256c713] 1/3044  (idx,y) = (1, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1256c713] 2/3044  (idx,y) = (2, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1256c713] 3/3044  (idx,y) = (3, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1256c713] 4/3044  (idx,y) = (4, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1256c713] 5/3044  (idx,y) = (5, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1256c713] 6/3044  (idx,y) = (6, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1256c713] 7/3044  (idx,y) = (7, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1256c713] 8/3044  (idx,y) = (8, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1256c713] 9/3044  (idx,y) = (9, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1256c713] 10/3044  (idx,y) = (10, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1256c713] 11/3044  (idx,y) = (11, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1256c713] 12/3044  (idx,y) = (12, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1256c713] 13/3044  (idx,y) = (13, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1256c713] 14/3044  (idx,y) = (14, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1256c713] 15/3044  (idx,y) = (15, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1256c713] 16/3044  (idx,y) = (16, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1256c713] 17/3044  (idx,y) = (17, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1256c713] 18/3044  (idx,y) = (18, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f1256c713] 19/3044  (idx,y) = (19, 1)
        prior mean=[0]
        prior precision=[0.001]
        compute=[1]
        output:
            summary=[1]
            return.marginals=[1]
            nquantiles=[3]  [ 0.025 0.5 0.975 ]
            ncdf=[0]  [ ]
    section=[13] name=[log_LII_quant(0.337,2.3] type=[LINEAR]
    inla_parse_linear...
        section[log_LII_quant(0.337,2.3]
        dir=[fixed.effect00000010]
        file for covariates=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7f27b9cc]
        read n=[6088] entries from file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7f27b9cc]
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7f27b9cc] 0/3044  (idx,y) = (0, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7f27b9cc] 1/3044  (idx,y) = (1, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7f27b9cc] 2/3044  (idx,y) = (2, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7f27b9cc] 3/3044  (idx,y) = (3, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7f27b9cc] 4/3044  (idx,y) = (4, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7f27b9cc] 5/3044  (idx,y) = (5, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7f27b9cc] 6/3044  (idx,y) = (6, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7f27b9cc] 7/3044  (idx,y) = (7, 1)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7f27b9cc] 8/3044  (idx,y) = (8, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7f27b9cc] 9/3044  (idx,y) = (9, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7f27b9cc] 10/3044  (idx,y) = (10, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7f27b9cc] 11/3044  (idx,y) = (11, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7f27b9cc] 12/3044  (idx,y) = (12, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7f27b9cc] 13/3044  (idx,y) = (13, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7f27b9cc] 14/3044  (idx,y) = (14, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7f27b9cc] 15/3044  (idx,y) = (15, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7f27b9cc] 16/3044  (idx,y) = (16, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7f27b9cc] 17/3044  (idx,y) = (17, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7f27b9cc] 18/3044  (idx,y) = (18, 0)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f7f27b9cc] 19/3044  (idx,y) = (19, 0)
        prior mean=[0]
        prior precision=[0.001]
        compute=[1]
        output:
            summary=[1]
            return.marginals=[1]
            nquantiles=[3]  [ 0.025 0.5 0.975 ]
            ncdf=[0]  [ ]
    section=[14] name=[Lit_rate_demean] type=[LINEAR]
    inla_parse_linear...
        section[Lit_rate_demean]
        dir=[fixed.effect00000011]
        file for covariates=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f917414c]
        read n=[6088] entries from file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f917414c]
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f917414c] 0/3044  (idx,y) = (0, -0.057515)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f917414c] 1/3044  (idx,y) = (1, 0.0439105)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f917414c] 2/3044  (idx,y) = (2, 0.00388049)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f917414c] 3/3044  (idx,y) = (3, -0.00393435)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f917414c] 4/3044  (idx,y) = (4, -0.0287495)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f917414c] 5/3044  (idx,y) = (5, -0.00862934)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f917414c] 6/3044  (idx,y) = (6, 0.0753386)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f917414c] 7/3044  (idx,y) = (7, 0.0304397)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f917414c] 8/3044  (idx,y) = (8, 0.0574549)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f917414c] 9/3044  (idx,y) = (9, -0.00361096)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f917414c] 10/3044  (idx,y) = (10, 0.0301058)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f917414c] 11/3044  (idx,y) = (11, 0.0421761)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f917414c] 12/3044  (idx,y) = (12, 0.0875771)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f917414c] 13/3044  (idx,y) = (13, -0.00914456)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f917414c] 14/3044  (idx,y) = (14, 0.0715713)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f917414c] 15/3044  (idx,y) = (15, 0.0595273)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f917414c] 16/3044  (idx,y) = (16, 0.0674131)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f917414c] 17/3044  (idx,y) = (17, 0.0664691)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f917414c] 18/3044  (idx,y) = (18, 0.0644035)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f917414c] 19/3044  (idx,y) = (19, 0.0203868)
        prior mean=[0]
        prior precision=[0.001]
        compute=[1]
        output:
            summary=[1]
            return.marginals=[1]
            nquantiles=[3]  [ 0.025 0.5 0.975 ]
            ncdf=[0]  [ ]
    section=[15] name=[Perc_branca_demean] type=[LINEAR]
    inla_parse_linear...
        section[Perc_branca_demean]
        dir=[fixed.effect00000012]
        file for covariates=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f55bfe93d]
        read n=[6088] entries from file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f55bfe93d]
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f55bfe93d] 0/3044  (idx,y) = (0, -0.129052)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f55bfe93d] 1/3044  (idx,y) = (1, 0.00306269)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f55bfe93d] 2/3044  (idx,y) = (2, 0.00328586)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f55bfe93d] 3/3044  (idx,y) = (3, -0.104188)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f55bfe93d] 4/3044  (idx,y) = (4, -0.0674784)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f55bfe93d] 5/3044  (idx,y) = (5, 0.056489)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f55bfe93d] 6/3044  (idx,y) = (6, -0.00537394)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f55bfe93d] 7/3044  (idx,y) = (7, 0.0141822)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f55bfe93d] 8/3044  (idx,y) = (8, 0.0526717)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f55bfe93d] 9/3044  (idx,y) = (9, -0.0683338)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f55bfe93d] 10/3044  (idx,y) = (10, 0.000844842)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f55bfe93d] 11/3044  (idx,y) = (11, 0.0363403)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f55bfe93d] 12/3044  (idx,y) = (12, 0.0843284)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f55bfe93d] 13/3044  (idx,y) = (13, 0.0119034)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f55bfe93d] 14/3044  (idx,y) = (14, 0.132056)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f55bfe93d] 15/3044  (idx,y) = (15, 0.0669073)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f55bfe93d] 16/3044  (idx,y) = (16, 0.061721)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f55bfe93d] 17/3044  (idx,y) = (17, 0.0317377)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f55bfe93d] 18/3044  (idx,y) = (18, 0.0831232)
        file=[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/data.files/filef0f55bfe93d] 19/3044  (idx,y) = (19, -0.0500955)
        prior mean=[0]
        prior precision=[0.001]
        compute=[1]
        output:
            summary=[1]
            return.marginals=[1]
            nquantiles=[3]  [ 0.025 0.5 0.975 ]
            ncdf=[0]  [ ]
    Index table: number of entries[14], total length[9144]
        tag                            start-index     length
        Predictor                               0       3044
        bymID                                3044       6088
        (Intercept)                          9132          1
        log_inc_quant(6.95,7.3               9133          1
        log_inc_quant(7.3,7.81               9134          1
        log_inc_quant(7.81,9.99              9135          1
        ICE_quant(-0.185,-0.0955             9136          1
        ICE_quant(-0.0955,-0.00566           9137          1
        ICE_quant(-0.00566,0.888             9138          1
        log_LII_quant(-0.169,0.07            9139          1
        log_LII_quant(0.07,0.337             9140          1
        log_LII_quant(0.337,2.3              9141          1
        Lit_rate_demean                      9142          1
        Perc_branca_demean                   9143          1
    parse section=[17] name=[INLA.Parameters] type=[INLA]
    inla_parse_INLA...
        section[INLA.Parameters]
            lincomb.derived.only = [Yes]
            lincomb.derived.correlation.matrix = [No]
        global_node.factor = 2.000
        global_node.degree = 2147483647
        reordering = -1
Contents of ai_param 0x7fb389d0b8e0
    Optimiser: DEFAULT METHOD
        Option for domin-BFGS: epsx = 0.005
        Option for domin-BFGS: epsf = 1e-05 (rounding error)
        Option for domin-BFGS: epsg = 0.005
        Option for GSL-BFGS2: tol  = 0.1
        Option for GSL-BFGS2: step_size = 1
        Option for GSL-BFGS2: epsx = 0.005
        Option for GSL-BFGS2: epsf = 0.000353553
        Option for GSL-BFGS2: epsg = 0.005
        Restart: 0
        Mode known: No
    Gaussian approximation:
        abserr_func = 0.0005
        abserr_step = 0.0005
        optpar_fp = 0
        optpar_nr_step_factor = -0.1
    Gaussian data: No
    Strategy:   Use a mean-skew corrected Gaussian by fitting a Skew-Normal
    Fast mode:  On
    Use linear approximation to log(|Q +c|)? Yes
        Method:  Compute the derivative exact
    Parameters for improved approximations
        Number of points evaluate:   9
        Step length to compute derivatives numerically:  0.000100002
        Stencil to compute derivatives numerically:  5
        Cutoff value to construct local neigborhood:     0.0001
    Log calculations:    On
    Log calculated marginal for the hyperparameters:     On
    Integration strategy:    Automatic (GRID for dim(theta)=1 and 2 and otherwise CCD)
        f0 (CCD only):   1.100000
        dz (GRID only):  0.750000
        Adjust weights (GRID only):  On
        Difference in log-density limit (GRID only):     6.000000
        Skip configurations with (presumed) small density (GRID only):   On
    Gradient is computed using Central difference with step-length 0.010000
    Hessian is computed using Central difference with step-length 0.100000
    Hessian matrix is forced to be a diagonal matrix? [No]
    Compute effective number of parameters? [Yes]
    Perform a Monte Carlo error-test? [No]
    Interpolator [Auto]
    CPO required diff in log-density [3]
    Stupid search mode:
        Status     [On]
        Max iter   [1000]
        Factor     [1.05]
    Numerical integration of hyperparameters:
        Maximum number of function evaluations [100000]
        Relative error ....................... [1e-05]
        Absolute error ....................... [1e-06]
    To stabilise the numerical optimisation:
        Minimum value of the -Hessian [-inf]
    CPO manual calculation[No]
    Laplace-correction is Disabled.

inla_build: check for unused entries in[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/Model.ini]
inla_INLA...
    Strategy = [DEFAULT]
    Size is [9144]
    Chose OpenMP-strategy [LARGE]
    Chose density-strategy [HIGH]
    Size of graph=[9144] constraints=[1]
    Found optimal reordering=[amdc] nnz(L)=[116632] and use_global_nodes(user)=[no]
    List of hyperparameters: 
        theta[0] = [Log precision for bymID (idd component)]
        theta[1] = [Log precision for bymID (spatial component)]
Optimise using DEFAULT METHOD
max.logdens= -11670.458086 fn= 1 theta= 3.990000 4.000000  range=[-1.922 3.256]
max.logdens= -10288.103692 fn= 5 theta= 3.017731 3.812525  range=[-2.095 4.093]
max.logdens= -10286.780733 fn= 6 theta= 3.017731 3.802525  range=[-2.095 4.093]
max.logdens= -10273.840958 fn= 8 theta= 3.007731 3.812525  range=[-2.097 4.099]
max.logdens= -8339.572897 fn= 10 theta= 1.023300 3.431870  range=[-2.321 5.106]
max.logdens= -8339.476174 fn= 11 theta= 1.023300 3.421870  range=[-2.320 5.106]
max.logdens= -8336.510453 fn= 13 theta= 1.013300 3.431870  range=[-2.322 5.108]
max.logdens= -8272.652350 fn= 16 theta= 0.528709 3.337473  range=[-2.391 5.186]
max.logdens= -8272.636538 fn= 17 theta= 0.528709 3.327473  range=[-2.391 5.186]
max.logdens= -8272.314532 fn= 19 theta= 0.538709 3.337473  range=[-2.390 5.185]
Iter=1 |grad|=37.1 |x-x.old|=2.5 |f-f.old|=3.41e+03 
max.logdens= -8271.726058 fn= 21 theta= 0.720367 2.356011  range=[-2.311 5.164]
max.logdens= -8271.684499 fn= 22 theta= 0.720367 2.346011  range=[-2.310 5.164]
max.logdens= -8271.048353 fn= 23 theta= 0.710367 2.356011  range=[-2.312 5.165]
max.logdens= -8270.181173 fn= 26 theta= 0.637018 2.782835  range=[-2.347 5.174]
max.logdens= -8270.075973 fn= 27 theta= 0.637018 2.772835  range=[-2.347 5.174]
max.logdens= -8269.873145 fn= 29 theta= 0.627018 2.782835  range=[-2.349 5.175]
Iter=2 |grad|=20.5 |x-x.old|=0.358 |f-f.old|=2.54 
max.logdens= -8266.203308 fn= 36 theta= 0.652074 1.840531  range=[-2.292 5.176]
max.logdens= -8266.105033 fn= 37 theta= 0.652074 1.830531  range=[-2.292 5.176]
max.logdens= -8266.029120 fn= 38 theta= 0.642074 1.840531  range=[-2.294 5.177]
max.logdens= -8265.501163 fn= 42 theta= 0.659774 1.547367  range=[-2.274 5.177]
max.logdens= -8265.347703 fn= 43 theta= 0.659774 1.537367  range=[-2.274 5.177]
max.logdens= -8265.219932 fn= 47 theta= 0.663684 1.398521  range=[-2.265 5.178]
max.logdens= -8265.211772 fn= 48 theta= 0.663684 1.388521  range=[-2.264 5.178]
max.logdens= -8265.208982 fn= 52 theta= 0.664443 1.369612  range=[-2.263 5.178]
Iter=3 |grad|=1.48 |x-x.old|=1.04 |f-f.old|=4.9 
max.logdens= -8265.206218 fn= 59 theta= 0.667868 1.348524  range=[-2.261 5.178]
max.logdens= -8265.206095 fn= 64 theta= 0.668249 1.346177  range=[-2.261 5.178]
Iter=4 |grad|=0.339 |x-x.old|=0.0168 |f-f.old|=0.00289 
max.logdens= -8265.206064 fn= 74 theta= 0.668249 1.346177  range=[-2.261 5.178]
max.logdens= -8265.206058 fn= 80 theta= 0.668249 1.346177  range=[-2.261 5.178]
Iter=5 |grad|=0.339 |x-x.old|=1.79e-08(pass) |f-f.old|=3.54e-05(pass) Reached numerical limit!
Number of function evaluations = 90
Compute the Hessian using central differences and step_size[0.1]. Matrix-type [dense]

   603.265000    50.522614
    50.522614    12.868753
Eigenvectors of the Hessian
    0.996411    -0.084651
    0.084651    0.996411
Eigenvalues of the Hessian
    607.557221
    8.576532
StDev/Correlation matrix (scaled inverse Hessian)
     0.049696    -0.573408
                  0.340255
Compute corrected stdev for theta[0]: negative 0.985176  positive 0.998673
Compute corrected stdev for theta[1]: negative 0.809632  positive 1.132727
max.logdens= -8265.206087 fn= 104 theta= 0.668249 1.346177  range=[-2.261 5.178]
    config  0=[  0.00  0.00] log(rel.dens)=-0.12, [3] accept, compute, 10.16s
    config  1=[  0.00 -0.75] log(rel.dens)=-0.43, [2] accept, compute, 10.19s
    config  2=[ -0.75  0.00] log(rel.dens)=-0.36, [1] accept, compute, 10.25s
    config  3=[  0.75  0.00] log(rel.dens)=-0.29, [0] accept, compute, 10.52s
    config  4=[ -0.75  0.75] log(rel.dens)=-0.65, [2] accept, compute, 10.44s
    config  5=[  0.00  0.75] log(rel.dens)=-0.25, [3] accept, compute, 10.66s
    config  6=[ -0.75 -0.75] log(rel.dens)=-0.66, [1] accept, compute, 10.64s
    config  7=[  0.75 -0.75] log(rel.dens)=-0.59, [0] accept, compute, 10.82s
    config  8=[  0.75  0.75] log(rel.dens)=-0.51, [2] accept, compute, 10.23s
    config  9=[  0.00 -1.50] log(rel.dens)=-1.64, [3] accept, compute, 10.19s
    config 10=[ -1.50  0.00] log(rel.dens)=-1.14, [1] accept, compute, 10.23s
    config 11=[  1.50  0.00] log(rel.dens)=-1.11, [0] accept, compute, 10.23s
    config 12=[  0.00  1.50] log(rel.dens)=-0.91, [2] accept, compute, 9.97s
    config 13=[ -0.75  1.50] log(rel.dens)=-1.57, [3] accept, compute, 10.07s
    config 14=[  0.75 -1.50] log(rel.dens)=-1.75, [1] accept, compute, 10.06s
    config 15=[ -0.75 -1.50] log(rel.dens)=-2.10, [0] accept, compute, 10.26s
    config 16=[  0.75  1.50] log(rel.dens)=-1.01, [2] accept, compute, 10.13s
    config 17=[ -1.50 -0.75] log(rel.dens)=-1.58, [3] accept, compute, 10.42s
    config 18=[  1.50 -0.75] log(rel.dens)=-1.37, [1] accept, compute, 10.33s
    config 19=[ -1.50  0.75] log(rel.dens)=-1.62, [0] accept, compute, 10.37s
    config 20=[  1.50  0.75] log(rel.dens)=-1.28, [2] accept, compute, 10.32s
    config 21=[  1.50  1.50] log(rel.dens)=-1.80, [1] accept, compute, 10.21s
    config 22=[ -1.50 -1.50] log(rel.dens)=-2.84, [3] accept, compute, 10.23s
    config 23=[  1.50 -1.50] log(rel.dens)=-2.50, [0] accept, compute, 10.23s
    config 24=[ -1.50  1.50] log(rel.dens)=-2.61, [2] accept, compute, 9.96s
    config 25=[  0.00 -2.25] log(rel.dens)=-3.88, [1] accept, compute, 10.17s
    config 26=[  2.25  0.00] log(rel.dens)=-2.45, [3] accept, compute, 10.17s
    config 27=[ -2.25  0.00] log(rel.dens)=-2.79, [0] accept, compute, 10.05s
    config 28=[  0.00  2.25] log(rel.dens)=-1.87, [2] accept, compute, 10.19s
    config 29=[ -0.75 -2.25] log(rel.dens)=-4.47, [3] accept, compute, 10.20s
    config 30=[  2.25  0.75] log(rel.dens)=-2.61, [1] accept, compute, 10.27s
    config 31=[  0.75 -2.25] log(rel.dens)=-4.00, [0] accept, compute, 10.19s
    config 32=[ -2.25 -0.75] log(rel.dens)=-2.83, [2] accept, compute, 10.49s
    config 33=[  2.25 -0.75] log(rel.dens)=-2.62, [3] accept, compute, 10.32s
    config 34=[ -0.75  2.25] log(rel.dens)=-2.74, [1] accept, compute, 10.40s
    config 35=[ -2.25  0.75] log(rel.dens)=-2.96, [0] accept, compute, 10.51s
    config 36=[  0.75  2.25] log(rel.dens)=-1.77, [2] accept, compute, 10.71s
    config 37=[ -2.25 -1.50] log(rel.dens)=-4.23, [3] accept, compute, 10.70s
    config 38=[  2.25 -1.50] log(rel.dens)=-3.35, [1] accept, compute, 10.82s
    config 39=[ -1.50 -2.25] log(rel.dens)=-5.54, [0] accept, compute, 10.76s
    config 40=[  2.25  1.50] log(rel.dens)=-3.04, [2] accept, compute, 11.06s
    config 41=[  1.50 -2.25] log(rel.dens)=-4.17, [1] accept, compute, 11.23s
    config 42=[ -1.50  2.25] log(rel.dens)=-3.70, [3] accept, compute, 11.63s
    config 43=[ -2.25  1.50] log(rel.dens)=-4.02, [0] accept, compute, 11.21s
    config 44=[  0.00 -3.00] log(rel.dens)=-7.93, reject, 0.27s
    config 45=[  1.50  2.25] log(rel.dens)=-2.33, [2] accept, compute, 10.14s
    config 46=[  0.00  3.00] log(rel.dens)=-2.98, [1] accept, compute, 10.24s
    config 47=[  3.00  0.00] log(rel.dens)=-4.37, [3] accept, compute, 10.10s
    config 48=[ -3.00  0.00] log(rel.dens)=-4.43, [0] accept, compute, 10.23s
    config 49=[ -3.00  0.75] log(rel.dens)=-5.00, [2] accept, compute, 10.20s
    config 50=[  3.00  0.75] log(rel.dens)=-4.87, [1] accept, compute, 10.20s
    config 51=[ -0.75  3.00] log(rel.dens)=-3.85, [3] accept, compute, 10.32s
    config 52=[  0.75  3.00] log(rel.dens)=-2.71, [0] accept, compute, 10.18s
    config 53=[  3.00 -0.75] log(rel.dens)=-4.44, [2] accept, compute, 10.36s
    config 54=[ -2.25 -2.25] log(rel.dens)=-7.09, reject, 0.28s
    config 55=[ -3.00 -0.75] log(rel.dens)=-4.72, [1] accept, compute, 10.29s
    config 56=[  2.25  2.25] log(rel.dens)=-3.66, [3] accept, compute, 10.30s
    config 57=[ -3.00 -1.50] log(rel.dens)=-6.15, reject, 0.26s
    config 58=[  2.25 -2.25] log(rel.dens)=-4.97, [0] accept, compute, 10.45s
    config 59=[ -2.25  2.25] log(rel.dens)=-5.52, [2] accept, compute, 10.53s
    config 60=[ -3.00  1.50] log(rel.dens)=-6.22, reject, 0.21s
    config 61=[ -1.50  3.00] log(rel.dens)=-5.31, [1] accept, compute, 10.54s
    config 62=[  3.00 -2.25] log(rel.dens)=-6.28, reject, 0.30s
    config 63=[  3.00  1.50] log(rel.dens)=-4.83, [3] accept, compute, 10.51s
    config 64=[  1.50  3.00] log(rel.dens)=-3.04, [0] accept, compute, 10.39s
    config 65=[  3.00 -1.50] log(rel.dens)=-4.98, [2] accept, compute, 10.29s
    config 66=[ -2.25  3.00] log(rel.dens)=-7.37, reject, 0.28s
    config 67=[  3.75  0.00] log(rel.dens)=-6.84, reject, 0.30s
    config 68=[  2.25  3.00] log(rel.dens)=-4.03, [3] accept, compute, 10.21s
    config 69=[ -3.75  0.00] log(rel.dens)=-6.90, reject, 0.30s
    config 70=[  3.00  2.25] log(rel.dens)=-5.17, [1] accept, compute, 10.57s
    config 71=[  0.00  3.75] log(rel.dens)=-4.39, [0] accept, compute, 10.19s
    config 72=[ -1.50  3.75] log(rel.dens)=-7.18, reject, 0.27s
    config 73=[ -0.75  3.75] log(rel.dens)=-5.69, [3] accept, compute, 11.03s
    config 74=[  0.75  3.75] log(rel.dens)=-3.78, [2] accept, compute, 11.00s
    config 75=[  1.50  3.75] log(rel.dens)=-3.91, [0] accept, compute, 11.03s
    config 76=[ -0.75  4.50] log(rel.dens)=-7.38, reject, 0.20s
    config 77=[  3.00  3.00] log(rel.dens)=-5.51, [1] accept, compute, 12.15s
    config 78=[  2.25  3.75] log(rel.dens)=-4.74, [3] accept, compute, 10.29s
    config 79=[  0.00  4.50] log(rel.dens)=-5.83, [2] accept, compute, 10.57s
    config 80=[  0.75  4.50] log(rel.dens)=-5.03, [0] accept, compute, 10.67s
    config 81=[  0.00  5.25] log(rel.dens)=-7.45, reject, 0.20s
    config 82=[  3.00  4.50] log(rel.dens)=-6.45, reject, 0.20s
    config 83=[  1.50  4.50] log(rel.dens)=-4.89, [1] accept, compute, 10.26s
    config 84=[  3.00  3.75] log(rel.dens)=-5.86, [3] accept, compute, 6.37s
    config 85=[  2.25  4.50] log(rel.dens)=-5.28, [2] accept, compute, 6.11s
Combine the densities with relative weights:
    config  0/74=[  0.00  0.00] weight = 1.000 adjusted weight = 0.948  neff = 2011.50
    config  1/74=[  0.00 -0.75] weight = 0.735 adjusted weight = 0.706  neff = 2012.22
    config  2/74=[ -0.75  0.00] weight = 0.784 adjusted weight = 0.753  neff = 2025.49
    config  3/74=[  0.75  0.00] weight = 0.839 adjusted weight = 0.805  neff = 1997.28
    config  4/74=[ -0.75  0.75] weight = 0.590 adjusted weight = 0.574  neff = 2027.31
    config  5/74=[  0.00  0.75] weight = 0.876 adjusted weight = 0.841  neff = 2013.03
    config  6/74=[ -0.75 -0.75] weight = 0.585 adjusted weight = 0.568  neff = 2025.91
    config  7/74=[  0.75 -0.75] weight = 0.627 adjusted weight = 0.609  neff = 1998.32
    config  8/74=[  0.75  0.75] weight = 0.679 adjusted weight = 0.661  neff = 1998.71
    config  9/74=[  0.00 -1.50] weight = 0.218 adjusted weight = 0.218  neff = 2015.95
    config 10/74=[ -1.50  0.00] weight = 0.359 adjusted weight = 0.358  neff = 2039.36
    config 11/74=[  1.50  0.00] weight = 0.372 adjusted weight = 0.371  neff = 1983.06
    config 12/74=[  0.00  1.50] weight = 0.452 adjusted weight = 0.451  neff = 2016.59
    config 13/74=[ -0.75  1.50] weight = 0.235 adjusted weight = 0.237  neff = 2031.15
    config 14/74=[  0.75 -1.50] weight = 0.195 adjusted weight = 0.197  neff = 2002.47
    config 15/74=[ -0.75 -1.50] weight = 0.138 adjusted weight = 0.140  neff = 2029.38
    config 16/74=[  0.75  1.50] weight = 0.411 adjusted weight = 0.415  neff = 2002.08
    config 17/74=[ -1.50 -0.75] weight = 0.231 adjusted weight = 0.234  neff = 2039.66
    config 18/74=[  1.50 -0.75] weight = 0.287 adjusted weight = 0.290  neff = 1984.41
    config 19/74=[ -1.50  0.75] weight = 0.223 adjusted weight = 0.225  neff = 2041.49
    config 20/74=[  1.50  0.75] weight = 0.314 adjusted weight = 0.317  neff = 1984.24
    config 21/74=[  1.50  1.50] weight = 0.185 adjusted weight = 0.195  neff = 1987.57
    config 22/74=[ -1.50 -1.50] weight = 0.066 adjusted weight = 0.069  neff = 2042.54
    config 23/74=[  1.50 -1.50] weight = 0.093 adjusted weight = 0.097  neff = 1989.05
    config 24/74=[ -1.50  1.50] weight = 0.083 adjusted weight = 0.087  neff = 2045.39
    config 25/74=[  0.00 -2.25] weight = 0.023 adjusted weight = 0.025  neff = 2023.02
    config 26/74=[  2.25  0.00] weight = 0.097 adjusted weight = 0.103  neff = 1968.71
    config 27/74=[ -2.25  0.00] weight = 0.069 adjusted weight = 0.073  neff = 2053.40
    config 28/74=[  0.00  2.25] weight = 0.174 adjusted weight = 0.185  neff = 2021.70
    config 29/74=[ -0.75 -2.25] weight = 0.013 adjusted weight = 0.014  neff = 2035.95
    config 30/74=[  2.25  0.75] weight = 0.083 adjusted weight = 0.089  neff = 1969.67
    config 31/74=[  0.75 -2.25] weight = 0.021 adjusted weight = 0.022  neff = 2010.22
    config 32/74=[ -2.25 -0.75] weight = 0.066 adjusted weight = 0.071  neff = 2053.12
    config 33/74=[  2.25 -0.75] weight = 0.082 adjusted weight = 0.088  neff = 1970.37
    config 34/74=[ -0.75  2.25] weight = 0.073 adjusted weight = 0.078  neff = 2036.36
    config 35/74=[ -2.25  0.75] weight = 0.058 adjusted weight = 0.063  neff = 2055.38
    config 36/74=[  0.75  2.25] weight = 0.192 adjusted weight = 0.207  neff = 2007.07
    config 37/74=[ -2.25 -1.50] weight = 0.016 adjusted weight = 0.018  neff = 2055.76
    config 38/74=[  2.25 -1.50] weight = 0.039 adjusted weight = 0.044  neff = 1975.21
    config 39/74=[ -1.50 -2.25] weight = 0.004 adjusted weight = 0.005  neff = 2048.82
    config 40/74=[  2.25  1.50] weight = 0.054 adjusted weight = 0.060  neff = 1972.80
    config 41/74=[  1.50 -2.25] weight = 0.017 adjusted weight = 0.019  neff = 1997.00
    config 42/74=[ -1.50  2.25] weight = 0.028 adjusted weight = 0.031  neff = 2050.49
    config 43/74=[ -2.25  1.50] weight = 0.020 adjusted weight = 0.023  neff = 2059.35
    config 44/74=[  1.50  2.25] weight = 0.109 adjusted weight = 0.122  neff = 1992.37
    config 45/74=[  0.00  3.00] weight = 0.057 adjusted weight = 0.066  neff = 2027.97
    config 46/74=[  3.00  0.00] weight = 0.014 adjusted weight = 0.016  neff = 1954.30
    config 47/74=[ -3.00  0.00] weight = 0.013 adjusted weight = 0.016  neff = 2066.88
    config 48/74=[ -3.00  0.75] weight = 0.008 adjusted weight = 0.009  neff = 2069.28
    config 49/74=[  3.00  0.75] weight = 0.009 adjusted weight = 0.010  neff = 1955.30
    config 50/74=[ -0.75  3.00] weight = 0.024 adjusted weight = 0.028  neff = 2042.50
    config 51/74=[  0.75  3.00] weight = 0.075 adjusted weight = 0.088  neff = 2013.31
    config 52/74=[  3.00 -0.75] weight = 0.013 adjusted weight = 0.015  neff = 1956.28
    config 53/74=[ -3.00 -0.75] weight = 0.010 adjusted weight = 0.012  neff = 2066.59
    config 54/74=[  2.25  2.25] weight = 0.029 adjusted weight = 0.034  neff = 1977.70
    config 55/74=[  2.25 -2.25] weight = 0.008 adjusted weight = 0.009  neff = 1983.84
    config 56/74=[ -2.25  2.25] weight = 0.005 adjusted weight = 0.005  neff = 2064.71
    config 57/74=[ -1.50  3.00] weight = 0.006 adjusted weight = 0.007  neff = 2056.89
    config 58/74=[  3.00  1.50] weight = 0.009 adjusted weight = 0.011  neff = 1957.91
    config 59/74=[  1.50  3.00] weight = 0.054 adjusted weight = 0.066  neff = 1998.53
    config 60/74=[  3.00 -1.50] weight = 0.008 adjusted weight = 0.009  neff = 1961.53
    config 61/74=[  2.25  3.00] weight = 0.020 adjusted weight = 0.026  neff = 1983.67
    config 62/74=[  3.00  2.25] weight = 0.006 adjusted weight = 0.008  neff = 1962.55
    config 63/74=[  0.00  3.75] weight = 0.014 adjusted weight = 0.018  neff = 2035.28
    config 64/74=[ -0.75  3.75] weight = 0.004 adjusted weight = 0.005  neff = 2049.96
    config 65/74=[  0.75  3.75] weight = 0.026 adjusted weight = 0.033  neff = 2020.53
    config 66/74=[  1.50  3.75] weight = 0.023 adjusted weight = 0.031  neff = 2005.76
    config 67/74=[  3.00  3.00] weight = 0.005 adjusted weight = 0.006  neff = 1968.58
    config 68/74=[  2.25  3.75] weight = 0.010 adjusted weight = 0.014  neff = 1990.94
    config 69/74=[  0.00  4.50] weight = 0.003 adjusted weight = 0.005  neff = 2043.20
    config 70/74=[  0.75  4.50] weight = 0.007 adjusted weight = 0.011  neff = 2028.54
    config 71/74=[  1.50  4.50] weight = 0.008 adjusted weight = 0.013  neff = 2013.79
    config 72/74=[  3.00  3.75] weight = 0.003 adjusted weight = 0.005  neff = 1975.71
    config 73/74=[  2.25  4.50] weight = 0.006 adjusted weight = 0.009  neff = 1998.83
Done.
Expected effective number of parameters: 2011.203(19.240),  eqv.#replicates: 1.514
DIC:
    Mean of Deviance................. 12183.6
    Deviance at Mean................. 10209.6
    Effective number of parameters... 1973.98
    DIC.............................. 14157.6
Marginal likelihood: Integration -8267.263924 Gaussian-approx -8267.647448
Compute the marginal for each of the 2 hyperparameters
Interpolation method: Auto
    Compute the marginal for theta[0] to theta[1] using numerical integration...
    Compute the marginal for theta[0] to theta[1] using numerical integration... Done.
Compute the marginal for the hyperparameters... done.
Store results in directory[/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/results.files]

Wall-clock time used on [/var/folders/_f/c7x33pyd15d2nc0t0rwwn9tw0000gn/T//RtmpyyVxGi/filef0f584f5756/Model.ini]
    Preparations    :   0.152 seconds
    Approx inference: 216.252 seconds [0.2|0.0|3.8|89.9|6.1]%
    Output          :   0.951 seconds
    ---------------------------------
    Total           : 217.356 seconds

formula_bym_8 <- y ~ 1 + f(bymID, model="bym", graph=CT_adj) + Perc_Wtr_Spply_Ntwrk + Perc_Garbage_Col_Serv + Perc_PPH_Elec + Lit_rate + log_mean_HH_inc + ICE + log_LII + Perc_branca

model_bym_8 <- inla(formula_bym_8, family="poisson", data=BYM_data_covar, E=E, control.predictor=list(compute=TRUE), verbose = TRUE)

formula_bym_9 <- y ~ 1 + f(bymID, model="bym", graph=CT_adj) + Perc_Garbage_Col_Serv + Lit_rate + log_mean_HH_inc + ICE_quant + Perc_branca

model_bym_9 <- inla(formula_bym_9, family="poisson", data=BYM_data_covar, E=E, control.predictor=list(compute=TRUE), verbose = TRUE)

summary(model_bym_1)

Call:
c("inla(formula = formula_bym_1, family = \"poisson\", data = BYM_data_covar, ",  "    E = E, verbose = TRUE, control.predictor = list(compute = TRUE))" )

Time used:
 Pre-processing    Running inla Post-processing           Total 
         1.5329        199.1192          1.2199        201.8720 

Fixed effects:
                   mean     sd 0.025quant 0.5quant 0.975quant    mode kld
(Intercept)      4.2557 0.2553     3.7528   4.2563     4.7551  4.2574   0
log_mean_HH_inc -0.6256 0.0344    -0.6929  -0.6256    -0.5580 -0.6258   0

Random effects:
Name      Model
 bymID   BYM model 

Model hyperparameters:
                                         mean    sd 0.025quant 0.5quant 0.975quant  mode
Precision for bymID (iid component)     1.958 0.094      1.776    1.957      2.146 1.958
Precision for bymID (spatial component) 3.818 1.177      2.112    3.612      6.675 3.236

Expected number of effective parameters(std dev): 2010.94(19.19)
Number of equivalent replicates : 1.514 

Marginal log-Likelihood:  -8222.09 
Posterior marginals for linear predictor and fitted values computed

summary(model_bym_2)

Call:
c("inla(formula = formula_bym_2, family = \"poisson\", data = BYM_data_covar, ",  "    E = E, verbose = TRUE, control.predictor = list(compute = TRUE))" )

Time used:
 Pre-processing    Running inla Post-processing           Total 
         1.7008        243.0247          1.4088        246.1342 

Fixed effects:
                              mean     sd 0.025quant 0.5quant 0.975quant    mode kld
(Intercept)                -0.0146 0.0343    -0.0821  -0.0146     0.0525 -0.0145   0
ICE_quant(-0.185,-0.0955   -0.2265 0.0454    -0.3156  -0.2265    -0.1376 -0.2265   0
ICE_quant(-0.0955,-0.00566 -0.4662 0.0479    -0.5604  -0.4662    -0.3722 -0.4662   0
ICE_quant(-0.00566,0.888   -0.9566 0.0644    -1.0832  -0.9566    -0.8304 -0.9565   0

Random effects:
Name      Model
 bymID   BYM model 

Model hyperparameters:
                                         mean    sd 0.025quant 0.5quant 0.975quant  mode
Precision for bymID (iid component)     1.986 0.097      1.799    1.985      2.180 1.984
Precision for bymID (spatial component) 2.468 0.601      1.546    2.378      3.886 2.203

Expected number of effective parameters(std dev): 2029.78(18.92)
Number of equivalent replicates : 1.50 

Marginal log-Likelihood:  -8270.07 
Posterior marginals for linear predictor and fitted values computed

summary(model_bym_3)

Call:
c("inla(formula = formula_bym_3, family = \"poisson\", data = BYM_data_covar, ",  "    E = E, verbose = TRUE, control.predictor = list(compute = TRUE))" )

Time used:
 Pre-processing    Running inla Post-processing           Total 
         1.3041        176.7624          0.6840        178.7505 

Fixed effects:
               mean     sd 0.025quant 0.5quant 0.975quant    mode kld
(Intercept) -0.4699 0.0173    -0.5040  -0.4698    -0.4362 -0.4697   0
log_LII      0.5143 0.0373     0.4411   0.5142     0.5876  0.5141   0

Random effects:
Name      Model
 bymID   BYM model 

Model hyperparameters:
                                         mean     sd 0.025quant 0.5quant 0.975quant   mode
Precision for bymID (iid component)     2.379 0.1424     2.1090    2.376      2.670 2.3701
Precision for bymID (spatial component) 1.033 0.1444     0.7801    1.022      1.349 0.9989

Expected number of effective parameters(std dev): 2028.34(18.82)
Number of equivalent replicates : 1.501 

Marginal log-Likelihood:  -8279.68 
Posterior marginals for linear predictor and fitted values computed

summary(model_bym_4)

Call:
c("inla(formula = formula_bym_4, family = \"poisson\", data = BYM_data_covar, ",  "    E = E, verbose = TRUE, control.predictor = list(compute = TRUE))" )

Time used:
 Pre-processing    Running inla Post-processing           Total 
         1.4813        328.0995          1.7753        331.3560 

Fixed effects:
                   mean     sd 0.025quant 0.5quant 0.975quant    mode kld
(Intercept)      1.4307 0.5091     0.4261   1.4323     2.4254  1.4356   0
log_mean_HH_inc -0.2626 0.0662    -0.3919  -0.2628    -0.1322 -0.2632   0
ICE             -1.5269 0.2366    -1.9932  -1.5264    -1.0641 -1.5253   0

Random effects:
Name      Model
 bymID   BYM model 

Model hyperparameters:
                                         mean     sd 0.025quant 0.5quant 0.975quant  mode
Precision for bymID (iid component)     1.940 0.0892      1.779    1.935      2.129 1.919
Precision for bymID (spatial component) 4.816 1.6323      2.332    4.583      8.664 4.141

Expected number of effective parameters(std dev): 2002.23(19.17)
Number of equivalent replicates : 1.52 

Marginal log-Likelihood:  -8206.72 
Posterior marginals for linear predictor and fitted values computed

summary(model_bym_5)

Call:
c("inla(formula = formula_bym_5, family = \"poisson\", data = BYM_data_covar, ",  "    E = E, verbose = TRUE, control.predictor = list(compute = TRUE))" )

Time used:
 Pre-processing    Running inla Post-processing           Total 
         1.7538        351.4770          1.9814        355.2122 

Fixed effects:
                   mean     sd 0.025quant 0.5quant 0.975quant    mode kld
(Intercept)      1.9154 0.5465     0.8356   1.9177     2.9820  1.9222   0
log_mean_HH_inc -0.3267 0.0712    -0.4657  -0.3270    -0.1862 -0.3275   0
ICE             -1.6101 0.2376    -2.0778  -1.6097    -1.1448 -1.6089   0
log_LII         -0.1266 0.0563    -0.2367  -0.1268    -0.0156 -0.1272   0

Random effects:
Name      Model
 bymID   BYM model 

Model hyperparameters:
                                         mean     sd 0.025quant 0.5quant 0.975quant  mode
Precision for bymID (iid component)     1.930 0.0851      1.768    1.927      2.103 1.922
Precision for bymID (spatial component) 5.569 2.0092      2.693    5.217     10.462 4.590

Expected number of effective parameters(std dev): 2001.86(19.23)
Number of equivalent replicates : 1.521 

Marginal log-Likelihood:  -8210.57 
Posterior marginals for linear predictor and fitted values computed

summary(model_bym_6)

Call:
c("inla(formula = formula_bym_6, family = \"poisson\", data = BYM_data_covar, ",  "    E = E, verbose = TRUE, control.predictor = list(compute = TRUE))" )

Time used:
 Pre-processing    Running inla Post-processing           Total 
         1.5947        217.9480          0.6745        220.2172 

Fixed effects:
               mean     sd 0.025quant 0.5quant 0.975quant    mode kld
(Intercept)  0.5034 0.0648     0.3761   0.5034     0.6305  0.5034   0
Perc_branca -2.4497 0.1701    -2.7843  -2.4496    -2.1165 -2.4492   0

Random effects:
Name      Model
 bymID   BYM model 

Model hyperparameters:
                                         mean     sd 0.025quant 0.5quant 0.975quant  mode
Precision for bymID (iid component)     1.996 0.0992      1.805    1.994      2.195 1.992
Precision for bymID (spatial component) 2.266 0.5237      1.449    2.193      3.489 2.048

Expected number of effective parameters(std dev): 2033.13(18.77)
Number of equivalent replicates : 1.497 

Marginal log-Likelihood:  -8269.96 
Posterior marginals for linear predictor and fitted values computed

summary(model_bym_7)

Call:
c("inla(formula = formula_bym_7, family = \"poisson\", data = BYM_data_covar, ",  "    E = E, verbose = TRUE, control.predictor = list(compute = TRUE))" )

Time used:
 Pre-processing    Running inla Post-processing           Total 
         1.4709        216.1419          1.1469        218.7597 

Fixed effects:
                         mean     sd 0.025quant 0.5quant 0.975quant    mode kld
(Intercept)            3.5010 0.5374     2.4364   3.5042     4.5475  3.5105   0
Perc_Wtr_Spply_Ntwrk   0.3220 0.1812    -0.0329   0.3216     0.6784  0.3210   0
Perc_Garbage_Col_Serv  0.1436 0.0958    -0.0440   0.1435     0.3320  0.1431   0
Perc_PPH_Elec         -0.3663 0.5553    -1.4455  -0.3702     0.7339 -0.3780   0
Lit_rate              -4.6523 0.3011    -5.2440  -4.6521    -4.0620 -4.6518   0

Random effects:
Name      Model
 bymID   BYM model 

Model hyperparameters:
                                         mean     sd 0.025quant 0.5quant 0.975quant  mode
Precision for bymID (iid component)     2.089 0.1071      1.884    2.087      2.305 2.085
Precision for bymID (spatial component) 1.959 0.4061      1.302    1.910      2.887 1.812

Expected number of effective parameters(std dev): 2023.18(19.17)
Number of equivalent replicates : 1.505 

Marginal log-Likelihood:  -8266.42 
Posterior marginals for linear predictor and fitted values computed

summary(model_bym_8)

Call:
c("inla(formula = formula_bym_8, family = \"poisson\", data = BYM_data_covar, ",  "    E = E, verbose = TRUE, control.predictor = list(compute = TRUE))" )

Time used:
 Pre-processing    Running inla Post-processing           Total 
         1.6956        467.6865          1.1383        470.5205 

Fixed effects:
                         mean     sd 0.025quant 0.5quant 0.975quant    mode kld
(Intercept)            2.5729 0.6673     1.2505   2.5770     3.8717  2.5851   0
Perc_Wtr_Spply_Ntwrk   0.0292 0.1769    -0.3173   0.0288     0.3771  0.0282   0
Perc_Garbage_Col_Serv  0.1834 0.0946    -0.0019   0.1832     0.3695  0.1829   0
Perc_PPH_Elec         -0.1044 0.5703    -1.2202  -0.1059     1.0182 -0.1087   0
Lit_rate              -1.8621 0.3805    -2.6091  -1.8622    -1.1156 -1.8622   0
log_mean_HH_inc       -0.1743 0.0809    -0.3326  -0.1744    -0.0152 -0.1747   0
ICE                   -1.3500 0.2513    -1.8443  -1.3497    -0.8578 -1.3491   0
log_LII               -0.1587 0.0550    -0.2664  -0.1588    -0.0505 -0.1590   0
Perc_branca           -0.7198 0.2177    -1.1474  -0.7197    -0.2928 -0.7196   0

Random effects:
Name      Model
 bymID   BYM model 

Model hyperparameters:
                                         mean     sd 0.025quant 0.5quant 0.975quant  mode
Precision for bymID (iid component)     1.916 0.0811      1.762    1.915      2.081 1.911
Precision for bymID (spatial component) 7.946 3.4837      3.320    7.232     16.670 6.040

Expected number of effective parameters(std dev): 1996.81(19.21)
Number of equivalent replicates : 1.524 

Marginal log-Likelihood:  -8214.82 
Posterior marginals for linear predictor and fitted values computed

BYM_data_ICE <- BYM_data_covar %>% mutate(raw_SMR = y / E) %>% mutate(log_SMR = log(raw_SMR)) 
ggplot(BYM_data_ICE, aes(x=ICE_quant, y=raw_SMR)) + geom_boxplot() + 
    coord_cartesian(ylim = c(0, 10)) + geom_hline(yintercept = 1.0)

ggplot(BYM_data_ICE, aes(x=ICE_quant, y=log_SMR)) + geom_boxplot() + geom_hline(yintercept = 0.0)

BYM_data_ICE <- BYM_data_ICE %>% group_by(ICE_quant) %>% summarize(mean_SMR = mean(raw_SMR, na.rm=TRUE))
ggplot(BYM_data_ICE, aes(x=ICE_quant, y=mean_SMR)) + geom_bar(stat = "identity", fill="firebrick3") + geom_hline(yintercept = 1.0)

BYM_data_inc <- BYM_data_covar %>% mutate(raw_SMR = y / E) %>% mutate(log_SMR = log(raw_SMR)) 
ggplot(BYM_data_inc, aes(x=log_inc_quant, y=raw_SMR)) + geom_boxplot() + 
    coord_cartesian(ylim = c(0, 10)) + geom_hline(yintercept = 1.0)